id sid tid token lemma pos cana-3756 1 1 communications communication NOUN cana-3756 1 2 on on ADP cana-3756 1 3 applied apply VERB cana-3756 1 4 nonlinear nonlinear ADJ cana-3756 1 5 analysis analysis NOUN cana-3756 1 6 issn issn NOUN cana-3756 1 7 : : PUNCT cana-3756 1 8 1074 1074 NUM cana-3756 1 9 - - PUNCT cana-3756 1 10 133x 133x NUM cana-3756 1 11 vol vol NOUN cana-3756 1 12 32 32 NUM cana-3756 1 13 no no NOUN cana-3756 1 14 . . PUNCT cana-3756 2 1 8s 8s PROPN cana-3756 2 2 ( ( PUNCT cana-3756 2 3 2025 2025 NUM cana-3756 2 4 ) ) PUNCT cana-3756 2 5 685 685 NUM cana-3756 2 6 https://internationalpubls.com https://internationalpubls.com X cana-3756 2 7 human human ADJ cana-3756 2 8 gender gender NOUN cana-3756 2 9 identification identification NOUN cana-3756 2 10 from from ADP cana-3756 2 11 facial facial ADJ cana-3756 2 12 images image NOUN cana-3756 2 13 : : PUNCT cana-3756 2 14 a a DET cana-3756 2 15 deep deep ADJ cana-3756 2 16 learning learning NOUN cana-3756 2 17 approach approach NOUN cana-3756 2 18 * * PUNCT cana-3756 2 19 1ponukumati 1ponukumati NUM cana-3756 2 20 jyothi1 jyothi1 PROPN cana-3756 2 21 dr dr PROPN cana-3756 2 22 . . PROPN cana-3756 2 23 dasari dasari PROPN cana-3756 2 24 haritha2 haritha2 PROPN cana-3756 2 25 , , PUNCT cana-3756 3 1 dr dr PROPN cana-3756 3 2 . . PROPN cana-3756 3 3 karuna karuna PROPN cana-3756 3 4 arava3 arava3 PROPN cana-3756 3 5 1research 1research NUM cana-3756 3 6 scholar scholar NOUN cana-3756 3 7 , , PUNCT cana-3756 3 8 department department NOUN cana-3756 3 9 of of ADP cana-3756 3 10 computer computer NOUN cana-3756 3 11 science science NOUN cana-3756 3 12 and and CCONJ cana-3756 3 13 engineering engineering NOUN cana-3756 3 14 , , PUNCT cana-3756 3 15 jntu jntu PROPN cana-3756 3 16 , , PUNCT cana-3756 3 17 kakinada kakinada PROPN cana-3756 3 18 533003 533003 NUM cana-3756 3 19 , , PUNCT cana-3756 3 20 andhra andhra PROPN cana-3756 3 21 pradesh pradesh PROPN cana-3756 3 22 , , PUNCT cana-3756 3 23 india india PROPN cana-3756 3 24 . . PUNCT cana-3756 4 1 mrspjyothi@gmail.com mrspjyothi@gmail.com X cana-3756 5 1 * * PUNCT cana-3756 5 2 1department 1department NUM cana-3756 5 3 of of ADP cana-3756 5 4 computer computer NOUN cana-3756 5 5 applications application NOUN cana-3756 5 6 , , PUNCT cana-3756 5 7 p.r p.r PROPN cana-3756 5 8 . . PROPN cana-3756 5 9 government government PROPN cana-3756 5 10 college college PROPN cana-3756 5 11 ( ( PUNCT cana-3756 5 12 a a NOUN cana-3756 5 13 ) ) PUNCT cana-3756 5 14 , , PUNCT cana-3756 5 15 kakinada kakinada PROPN cana-3756 5 16 , , PUNCT cana-3756 5 17 2professor 2professor NUM cana-3756 5 18 , , PUNCT cana-3756 5 19 department department NOUN cana-3756 5 20 of of ADP cana-3756 5 21 computer computer NOUN cana-3756 5 22 science science NOUN cana-3756 5 23 and and CCONJ cana-3756 5 24 engineering engineering NOUN cana-3756 5 25 , , PUNCT cana-3756 5 26 ucek ucek NOUN cana-3756 5 27 , , PUNCT cana-3756 5 28 jntu jntu PROPN cana-3756 5 29 , , PUNCT cana-3756 5 30 kakinada kakinada PROPN cana-3756 5 31 533003 533003 NUM cana-3756 5 32 , , PUNCT cana-3756 5 33 andhra andhra PROPN cana-3756 5 34 pradesh pradesh PROPN cana-3756 5 35 , , PUNCT cana-3756 5 36 india india PROPN cana-3756 5 37 . . PUNCT cana-3756 6 1 harithaphd1@gmail.com harithaphd1@gmail.com X cana-3756 7 1 3assistant 3assistant NUM cana-3756 7 2 professor professor NOUN cana-3756 7 3 , , PUNCT cana-3756 7 4 department department NOUN cana-3756 7 5 of of ADP cana-3756 7 6 computer computer NOUN cana-3756 7 7 science science NOUN cana-3756 7 8 and and CCONJ cana-3756 7 9 engineering engineering NOUN cana-3756 7 10 , , PUNCT cana-3756 7 11 ucek ucek NOUN cana-3756 7 12 , , PUNCT cana-3756 7 13 jntu jntu PROPN cana-3756 7 14 , , PUNCT cana-3756 7 15 kakinada kakinada PROPN cana-3756 7 16 533003 533003 NUM cana-3756 7 17 , , PUNCT cana-3756 7 18 andhra andhra PROPN cana-3756 7 19 pradesh pradesh PROPN cana-3756 7 20 , , PUNCT cana-3756 7 21 india india PROPN cana-3756 7 22 . . PUNCT cana-3756 8 1 karunagouthana@jntucek.ac.in karunagouthana@jntucek.ac.in PROPN cana-3756 8 2 article article NOUN cana-3756 8 3 history history NOUN cana-3756 8 4 : : PUNCT cana-3756 8 5 received receive VERB cana-3756 8 6 : : PUNCT cana-3756 8 7 06 06 NUM cana-3756 8 8 - - SYM cana-3756 8 9 11 11 NUM cana-3756 8 10 - - PUNCT cana-3756 8 11 2024 2024 NUM cana-3756 8 12 revised revise VERB cana-3756 8 13 : : PUNCT cana-3756 8 14 17 17 NUM cana-3756 8 15 - - SYM cana-3756 8 16 12 12 NUM cana-3756 8 17 - - PUNCT cana-3756 8 18 2024 2024 NUM cana-3756 8 19 accepted accept VERB cana-3756 8 20 : : PUNCT cana-3756 8 21 04 04 NUM cana-3756 8 22 - - PUNCT cana-3756 8 23 01 01 NUM cana-3756 8 24 - - PUNCT cana-3756 8 25 2025 2025 NUM cana-3756 8 26 abstract abstract NOUN cana-3756 8 27 : : PUNCT cana-3756 8 28 these these PRON cana-3756 8 29 in in ADP cana-3756 8 30 turn turn NOUN cana-3756 8 31 find find VERB cana-3756 8 32 broad broad ADJ cana-3756 8 33 applications application NOUN cana-3756 8 34 in in ADP cana-3756 8 35 security security NOUN cana-3756 8 36 , , PUNCT cana-3756 8 37 human human NOUN cana-3756 8 38 - - PUNCT cana-3756 8 39 computer computer NOUN cana-3756 8 40 interaction interaction NOUN cana-3756 8 41 , , PUNCT cana-3756 8 42 targeted target VERB cana-3756 8 43 marketing marketing NOUN cana-3756 8 44 , , PUNCT cana-3756 8 45 and and CCONJ cana-3756 8 46 social social ADJ cana-3756 8 47 analytics analytic NOUN cana-3756 8 48 . . PUNCT cana-3756 9 1 in in ADP cana-3756 9 2 this this DET cana-3756 9 3 work work NOUN cana-3756 9 4 , , PUNCT cana-3756 9 5 we we PRON cana-3756 9 6 propose propose VERB cana-3756 9 7 a a DET cana-3756 9 8 new new ADJ cana-3756 9 9 hybrid hybrid ADJ cana-3756 9 10 deep deep ADJ cana-3756 9 11 architecture architecture NOUN cana-3756 9 12 that that PRON cana-3756 9 13 reduces reduce VERB cana-3756 9 14 the the DET cana-3756 9 15 complexity complexity NOUN cana-3756 9 16 and and CCONJ cana-3756 9 17 improves improve VERB cana-3756 9 18 the the DET cana-3756 9 19 accuracy accuracy NOUN cana-3756 9 20 of of ADP cana-3756 9 21 gender gender NOUN cana-3756 9 22 classification classification NOUN cana-3756 9 23 . . PUNCT cana-3756 10 1 three three NUM cana-3756 10 2 different different ADJ cana-3756 10 3 models model NOUN cana-3756 10 4 are be AUX cana-3756 10 5 proposed propose VERB cana-3756 10 6 and and CCONJ cana-3756 10 7 tested test VERB cana-3756 10 8 , , PUNCT cana-3756 10 9 namely namely ADV cana-3756 10 10 : : PUNCT cana-3756 10 11 ( ( PUNCT cana-3756 10 12 1 1 X cana-3756 10 13 ) ) PUNCT cana-3756 10 14 a a DET cana-3756 10 15 pre pre ADJ cana-3756 10 16 - - ADJ cana-3756 10 17 trained train VERB cana-3756 10 18 efficientnetb2 efficientnetb2 NOUN cana-3756 10 19 model model NOUN cana-3756 10 20 with with ADP cana-3756 10 21 a a DET cana-3756 10 22 classifier classifier NOUN cana-3756 10 23 on on ADP cana-3756 10 24 top top NOUN cana-3756 10 25 performed perform VERB cana-3756 10 26 with with ADP cana-3756 10 27 an an DET cana-3756 10 28 average average ADJ cana-3756 10 29 accuracy accuracy NOUN cana-3756 10 30 of of ADP cana-3756 10 31 96.73 96.73 NUM cana-3756 10 32 % % NOUN cana-3756 10 33 , , PUNCT cana-3756 10 34 thus thus ADV cana-3756 10 35 proving prove VERB cana-3756 10 36 to to PART cana-3756 10 37 have have VERB cana-3756 10 38 strong strong ADJ cana-3756 10 39 capability capability NOUN cana-3756 10 40 in in ADP cana-3756 10 41 feature feature NOUN cana-3756 10 42 extraction extraction NOUN cana-3756 10 43 and and CCONJ cana-3756 10 44 classification classification NOUN cana-3756 10 45 ; ; PUNCT cana-3756 10 46 ( ( PUNCT cana-3756 10 47 2 2 X cana-3756 10 48 ) ) PUNCT cana-3756 10 49 a a DET cana-3756 10 50 hybrid hybrid ADJ cana-3756 10 51 architecture architecture NOUN cana-3756 10 52 that that PRON cana-3756 10 53 combines combine VERB cana-3756 10 54 mobilenetv2 mobilenetv2 PROPN cana-3756 10 55 and and CCONJ cana-3756 10 56 lstm lstm NOUN cana-3756 10 57 to to PART cana-3756 10 58 leverage leverage VERB cana-3756 10 59 the the DET cana-3756 10 60 benefits benefit NOUN cana-3756 10 61 of of ADP cana-3756 10 62 sequential sequential ADJ cana-3756 10 63 learning learning NOUN cana-3756 10 64 with with ADP cana-3756 10 65 an an DET cana-3756 10 66 average average ADJ cana-3756 10 67 performance performance NOUN cana-3756 10 68 of of ADP cana-3756 10 69 80 80 NUM cana-3756 10 70 % % NOUN cana-3756 10 71 which which PRON cana-3756 10 72 may may AUX cana-3756 10 73 indeed indeed ADV cana-3756 10 74 capture capture VERB cana-3756 10 75 the the DET cana-3756 10 76 temporal temporal ADJ cana-3756 10 77 dependencies dependency NOUN cana-3756 10 78 in in ADP cana-3756 10 79 facial facial ADJ cana-3756 10 80 representations representation NOUN cana-3756 10 81 ; ; PUNCT cana-3756 10 82 and and CCONJ cana-3756 10 83 ( ( PUNCT cana-3756 10 84 3 3 X cana-3756 10 85 ) ) PUNCT cana-3756 10 86 cnn cnn PROPN cana-3756 10 87 - - PUNCT cana-3756 10 88 lstm lstm PROPN cana-3756 10 89 , , PUNCT cana-3756 10 90 which which PRON cana-3756 10 91 combines combine VERB cana-3756 10 92 convolutional convolutional ADJ cana-3756 10 93 feature feature NOUN cana-3756 10 94 extraction extraction NOUN cana-3756 10 95 with with ADP cana-3756 10 96 sequential sequential ADJ cana-3756 10 97 processing processing NOUN cana-3756 10 98 , , PUNCT cana-3756 10 99 giving give VERB cana-3756 10 100 an an DET cana-3756 10 101 average average ADJ cana-3756 10 102 accuracy accuracy NOUN cana-3756 10 103 of of ADP cana-3756 10 104 85 85 NUM cana-3756 10 105 % % NOUN cana-3756 10 106 . . PUNCT cana-3756 11 1 our our PRON cana-3756 11 2 comparative comparative ADJ cana-3756 11 3 analysis analysis NOUN cana-3756 11 4 with with ADP cana-3756 11 5 existing exist VERB cana-3756 11 6 methodologies methodology NOUN cana-3756 11 7 reveals reveal VERB cana-3756 11 8 that that SCONJ cana-3756 11 9 the the DET cana-3756 11 10 proposed propose VERB cana-3756 11 11 model model NOUN cana-3756 11 12 using use VERB cana-3756 11 13 efficientnetb2 efficientnetb2 NOUN cana-3756 11 14 outperforms outperform NOUN cana-3756 11 15 conventional conventional ADJ cana-3756 11 16 approaches approach NOUN cana-3756 11 17 in in ADP cana-3756 11 18 terms term NOUN cana-3756 11 19 of of ADP cana-3756 11 20 classification classification NOUN cana-3756 11 21 accuracy accuracy NOUN cana-3756 11 22 as as ADV cana-3756 11 23 well well ADV cana-3756 11 24 as as ADP cana-3756 11 25 in in ADP cana-3756 11 26 terms term NOUN cana-3756 11 27 of of ADP cana-3756 11 28 computational computational ADJ cana-3756 11 29 efficiency efficiency NOUN cana-3756 11 30 , , PUNCT cana-3756 11 31 and and CCONJ cana-3756 11 32 hence hence ADV cana-3756 11 33 is be AUX cana-3756 11 34 more more ADV cana-3756 11 35 suitable suitable ADJ cana-3756 11 36 for for ADP cana-3756 11 37 real real ADJ cana-3756 11 38 - - PUNCT cana-3756 11 39 world world NOUN cana-3756 11 40 deployment deployment NOUN cana-3756 11 41 scenarios scenario NOUN cana-3756 11 42 with with ADP cana-3756 11 43 resource resource NOUN cana-3756 11 44 constraints constraint NOUN cana-3756 11 45 . . PUNCT cana-3756 12 1 moreover moreover ADV cana-3756 12 2 , , PUNCT cana-3756 12 3 many many ADJ cana-3756 12 4 experiments experiment NOUN cana-3756 12 5 has have AUX cana-3756 12 6 been be AUX cana-3756 12 7 conducted conduct VERB cana-3756 12 8 on on ADP cana-3756 12 9 benchmark benchmark NOUN cana-3756 12 10 datasets dataset NOUN cana-3756 12 11 which which PRON cana-3756 12 12 justifies justify VERB cana-3756 12 13 the the DET cana-3756 12 14 robustness robustness NOUN cana-3756 12 15 , , PUNCT cana-3756 12 16 generalizability generalizability NOUN cana-3756 12 17 of of ADP cana-3756 12 18 our our PRON cana-3756 12 19 proposed propose VERB cana-3756 12 20 models model NOUN cana-3756 12 21 . . PUNCT cana-3756 13 1 this this PRON cana-3756 13 2 presents present VERB cana-3756 13 3 more more ADV cana-3756 13 4 significant significant ADJ cana-3756 13 5 insights insight NOUN cana-3756 13 6 about about ADP cana-3756 13 7 the the DET cana-3756 13 8 development development NOUN cana-3756 13 9 of of ADP cana-3756 13 10 efficient efficient ADJ cana-3756 13 11 and and CCONJ cana-3756 13 12 high high ADV cana-3756 13 13 - - PUNCT cana-3756 13 14 performing perform VERB cana-3756 13 15 gender gender NOUN cana-3756 13 16 recognition recognition NOUN cana-3756 13 17 systems system NOUN cana-3756 13 18 based base VERB cana-3756 13 19 on on ADP cana-3756 13 20 deep deep ADJ cana-3756 13 21 learning learning NOUN cana-3756 13 22 from from ADP cana-3756 13 23 facial facial ADJ cana-3756 13 24 images image NOUN cana-3756 13 25 , , PUNCT cana-3756 13 26 thereby thereby ADV cana-3756 13 27 contributing contribute VERB cana-3756 13 28 to to ADP cana-3756 13 29 the the DET cana-3756 13 30 advancement advancement NOUN cana-3756 13 31 of of ADP cana-3756 13 32 research research NOUN cana-3756 13 33 in in ADP cana-3756 13 34 facial facial ADJ cana-3756 13 35 analysis analysis NOUN cana-3756 13 36 . . PUNCT cana-3756 14 1 keywords keyword NOUN cana-3756 14 2 : : PUNCT cana-3756 14 3 gender gender NOUN cana-3756 14 4 recognition recognition NOUN cana-3756 14 5 , , PUNCT cana-3756 14 6 deep deep ADJ cana-3756 14 7 learning learning NOUN cana-3756 14 8 , , PUNCT cana-3756 14 9 efficientnetb2 efficientnetb2 PROPN cana-3756 14 10 , , PUNCT cana-3756 14 11 cnn cnn PROPN cana-3756 14 12 - - PUNCT cana-3756 14 13 lstm lstm PROPN cana-3756 14 14 , , PUNCT cana-3756 14 15 mobilenetv2 mobilenetv2 NOUN cana-3756 14 16 , , PUNCT cana-3756 14 17 facial facial ADJ cana-3756 14 18 analysis analysis NOUN cana-3756 14 19 , , PUNCT cana-3756 14 20 computer computer NOUN cana-3756 14 21 vision vision NOUN cana-3756 14 22 , , PUNCT cana-3756 14 23 pattern pattern NOUN cana-3756 14 24 recognition recognition NOUN cana-3756 14 25 introduction introduction NOUN cana-3756 14 26 in in ADP cana-3756 14 27 computer computer NOUN cana-3756 14 28 vision vision NOUN cana-3756 14 29 , , PUNCT cana-3756 14 30 gender gender NOUN cana-3756 14 31 recognition recognition NOUN cana-3756 14 32 from from ADP cana-3756 14 33 facial facial ADJ cana-3756 14 34 images image NOUN cana-3756 14 35 is be AUX cana-3756 14 36 an an DET cana-3756 14 37 important important ADJ cana-3756 14 38 task task NOUN cana-3756 14 39 which which PRON cana-3756 14 40 has have VERB cana-3756 14 41 a a DET cana-3756 14 42 wide wide ADJ cana-3756 14 43 scope scope NOUN cana-3756 14 44 of of ADP cana-3756 14 45 applications application NOUN cana-3756 14 46 in in ADP cana-3756 14 47 different different ADJ cana-3756 14 48 fields field NOUN cana-3756 14 49 such such ADJ cana-3756 14 50 as as ADP cana-3756 14 51 security security NOUN cana-3756 14 52 systems system NOUN cana-3756 14 53 , , PUNCT cana-3756 14 54 human human NOUN cana-3756 14 55 - - PUNCT cana-3756 14 56 computer computer NOUN cana-3756 14 57 interaction interaction NOUN cana-3756 14 58 , , PUNCT cana-3756 14 59 demographic demographic ADJ cana-3756 14 60 analysis analysis NOUN cana-3756 14 61 , , PUNCT cana-3756 14 62 and and CCONJ cana-3756 14 63 personalized personalized ADJ cana-3756 14 64 content content NOUN cana-3756 14 65 recommendations recommendation NOUN cana-3756 14 66 . . PUNCT cana-3756 15 1 despite despite SCONJ cana-3756 15 2 the the DET cana-3756 15 3 significant significant ADJ cana-3756 15 4 amount amount NOUN cana-3756 15 5 of of ADP cana-3756 15 6 work work NOUN cana-3756 15 7 done do VERB cana-3756 15 8 in in ADP cana-3756 15 9 deep deep ADJ cana-3756 15 10 learning learning NOUN cana-3756 15 11 , , PUNCT cana-3756 15 12 it it PRON cana-3756 15 13 still still ADV cana-3756 15 14 remains remain VERB cana-3756 15 15 one one NUM cana-3756 15 16 of of ADP cana-3756 15 17 the the DET cana-3756 15 18 difficulties difficulty NOUN cana-3756 15 19 in in ADP cana-3756 15 20 being be AUX cana-3756 15 21 accurate accurate ADJ cana-3756 15 22 while while SCONJ cana-3756 15 23 being be AUX cana-3756 15 24 efficient efficient ADJ cana-3756 15 25 . . PUNCT cana-3756 16 1 most most ADV cana-3756 16 2 traditional traditional ADJ cana-3756 16 3 gender gender NOUN cana-3756 16 4 classification classification NOUN cana-3756 16 5 methods method NOUN cana-3756 16 6 fail fail VERB cana-3756 16 7 in in ADP cana-3756 16 8 pose pose NOUN cana-3756 16 9 , , PUNCT cana-3756 16 10 illumination illumination NOUN cana-3756 16 11 , , PUNCT cana-3756 16 12 occlusion occlusion NOUN cana-3756 16 13 , , PUNCT cana-3756 16 14 and and CCONJ cana-3756 16 15 other other ADJ cana-3756 16 16 real real ADJ cana-3756 16 17 - - PUNCT cana-3756 16 18 world world NOUN cana-3756 16 19 factors factor NOUN cana-3756 16 20 , , PUNCT cana-3756 16 21 which which PRON cana-3756 16 22 are be AUX cana-3756 16 23 usually usually ADV cana-3756 16 24 not not PART cana-3756 16 25 encountered encounter VERB cana-3756 16 26 in in ADP cana-3756 16 27 training training NOUN cana-3756 16 28 data datum NOUN cana-3756 16 29 . . PUNCT cana-3756 17 1 while while SCONJ cana-3756 17 2 deep deep ADJ cana-3756 17 3 learning learning NOUN cana-3756 17 4 models model NOUN cana-3756 17 5 have have AUX cana-3756 17 6 demonstrated demonstrate VERB cana-3756 17 7 superior superior ADJ cana-3756 17 8 performance performance NOUN cana-3756 17 9 , , PUNCT cana-3756 17 10 many many ADJ cana-3756 17 11 existing exist VERB cana-3756 17 12 architectures architecture NOUN cana-3756 17 13 require require VERB cana-3756 17 14 significant significant ADJ cana-3756 17 15 computational computational ADJ cana-3756 17 16 mailto:mrspjyothi@gmail.com mailto:mrspjyothi@gmail.com X cana-3756 17 17 mailto:harithaphd1@gmail.com mailto:harithaphd1@gmail.com PROPN cana-3756 17 18 mailto:karunagouthana@jntucek.ac.in mailto:karunagouthana@jntucek.ac.in PROPN cana-3756 17 19 communications communication NOUN cana-3756 17 20 on on ADP cana-3756 17 21 applied apply VERB cana-3756 17 22 nonlinear nonlinear ADJ cana-3756 17 23 analysis analysis NOUN cana-3756 17 24 issn issn NOUN cana-3756 17 25 : : PUNCT cana-3756 17 26 1074 1074 NUM cana-3756 17 27 - - PUNCT cana-3756 17 28 133x 133x NUM cana-3756 17 29 vol vol NOUN cana-3756 17 30 32 32 NUM cana-3756 17 31 no no NOUN cana-3756 17 32 . . PUNCT cana-3756 18 1 8s 8s PROPN cana-3756 18 2 ( ( PUNCT cana-3756 18 3 2025 2025 NUM cana-3756 18 4 ) ) PUNCT cana-3756 18 5 686 686 NUM cana-3756 18 6 https://internationalpubls.com https://internationalpubls.com NUM cana-3756 18 7 resources resource NOUN cana-3756 18 8 , , PUNCT cana-3756 18 9 making make VERB cana-3756 18 10 them they PRON cana-3756 18 11 impractical impractical ADJ cana-3756 18 12 for for ADP cana-3756 18 13 deployment deployment NOUN cana-3756 18 14 in in ADP cana-3756 18 15 resource resource NOUN cana-3756 18 16 - - PUNCT cana-3756 18 17 constrained constrain VERB cana-3756 18 18 environments environment NOUN cana-3756 18 19 or or CCONJ cana-3756 18 20 real real ADJ cana-3756 18 21 - - PUNCT cana-3756 18 22 time time NOUN cana-3756 18 23 applications application NOUN cana-3756 18 24 . . PUNCT cana-3756 19 1 it it PRON cana-3756 19 2 introduces introduce VERB cana-3756 19 3 novel novel ADJ cana-3756 19 4 hybrid hybrid ADJ cana-3756 19 5 deep deep ADJ cana-3756 19 6 learning learning NOUN cana-3756 19 7 architectures architecture NOUN cana-3756 19 8 capable capable ADJ cana-3756 19 9 of of ADP cana-3756 19 10 overcoming overcome VERB cana-3756 19 11 these these DET cana-3756 19 12 challenges challenge NOUN cana-3756 19 13 , , PUNCT cana-3756 19 14 which which PRON cana-3756 19 15 achieve achieve VERB cana-3756 19 16 recognition recognition NOUN cana-3756 19 17 accuracy accuracy NOUN cana-3756 19 18 optimized optimize VERB cana-3756 19 19 with with ADP cana-3756 19 20 the the DET cana-3756 19 21 efficiency efficiency NOUN cana-3756 19 22 of of ADP cana-3756 19 23 models model NOUN cana-3756 19 24 . . PUNCT cana-3756 20 1 one one NUM cana-3756 20 2 of of ADP cana-3756 20 3 our our PRON cana-3756 20 4 primary primary ADJ cana-3756 20 5 contributions contribution NOUN cana-3756 20 6 is be AUX cana-3756 20 7 an an DET cana-3756 20 8 efficientnetb2 efficientnetb2 NOUN cana-3756 20 9 - - PUNCT cana-3756 20 10 based base VERB cana-3756 20 11 model model NOUN cana-3756 20 12 with with ADP cana-3756 20 13 a a DET cana-3756 20 14 custom custom NOUN cana-3756 20 15 classifier classifier NOUN cana-3756 20 16 that that SCONJ cana-3756 20 17 , , PUNCT cana-3756 20 18 overall overall ADV cana-3756 20 19 , , PUNCT cana-3756 20 20 achieves achieve VERB cana-3756 20 21 the the DET cana-3756 20 22 state state NOUN cana-3756 20 23 - - PUNCT cana-3756 20 24 of of ADP cana-3756 20 25 - - PUNCT cana-3756 20 26 the the DET cana-3756 20 27 - - PUNCT cana-3756 20 28 art art NOUN cana-3756 20 29 accuracy accuracy NOUN cana-3756 20 30 keeping keep VERB cana-3756 20 31 computation computation NOUN cana-3756 20 32 feasible feasible ADJ cana-3756 20 33 . . PUNCT cana-3756 21 1 optimizing optimize VERB cana-3756 21 2 efficientnetb2 efficientnetb2 PROPN cana-3756 21 3 , , PUNCT cana-3756 21 4 with with ADP cana-3756 21 5 excellent excellent ADJ cana-3756 21 6 feature feature NOUN cana-3756 21 7 extraction extraction NOUN cana-3756 21 8 capability capability NOUN cana-3756 21 9 , , PUNCT cana-3756 21 10 through through ADP cana-3756 21 11 a a DET cana-3756 21 12 lightweight lightweight ADJ cana-3756 21 13 classification classification NOUN cana-3756 21 14 module module NOUN cana-3756 21 15 reduces reduce VERB cana-3756 21 16 computational computational ADJ cana-3756 21 17 complexity complexity NOUN cana-3756 21 18 without without ADP cana-3756 21 19 loss loss NOUN cana-3756 21 20 in in ADP cana-3756 21 21 performance performance NOUN cana-3756 21 22 . . PUNCT cana-3756 22 1 besides besides SCONJ cana-3756 22 2 this this DET cana-3756 22 3 architecture architecture NOUN cana-3756 22 4 , , PUNCT cana-3756 22 5 we we PRON cana-3756 22 6 develop develop VERB cana-3756 22 7 two two NUM cana-3756 22 8 hybrid hybrid ADJ cana-3756 22 9 models model NOUN cana-3756 22 10 : : PUNCT cana-3756 22 11 mobilenetv2 mobilenetv2 PROPN cana-3756 22 12 - - PUNCT cana-3756 22 13 lstm lstm PROPN cana-3756 22 14 and and CCONJ cana-3756 22 15 cnn cnn PROPN cana-3756 22 16 - - PUNCT cana-3756 22 17 lstm lstm PROPN cana-3756 22 18 architectures architecture NOUN cana-3756 22 19 . . PUNCT cana-3756 23 1 these these DET cana-3756 23 2 incorporate incorporate VERB cana-3756 23 3 cnns cnn NOUN cana-3756 23 4 that that PRON cana-3756 23 5 extract extract VERB cana-3756 23 6 spatial spatial ADJ cana-3756 23 7 feature feature NOUN cana-3756 23 8 extraction extraction NOUN cana-3756 23 9 and and CCONJ cana-3756 23 10 incorporate incorporate VERB cana-3756 23 11 lstm lstm ADJ cana-3756 23 12 networks network NOUN cana-3756 23 13 , , PUNCT cana-3756 23 14 which which PRON cana-3756 23 15 can can AUX cana-3756 23 16 represent represent VERB cana-3756 23 17 sequential sequential ADJ cana-3756 23 18 dependencies dependency NOUN cana-3756 23 19 for for ADP cana-3756 23 20 facial facial ADJ cana-3756 23 21 features feature NOUN cana-3756 23 22 . . PUNCT cana-3756 24 1 combining combine VERB cana-3756 24 2 all all DET cana-3756 24 3 these these DET cana-3756 24 4 techniques technique NOUN cana-3756 24 5 has have VERB cana-3756 24 6 the the DET cana-3756 24 7 potential potential NOUN cana-3756 24 8 of of ADP cana-3756 24 9 boosting boost VERB cana-3756 24 10 the the DET cana-3756 24 11 efficiency efficiency NOUN cana-3756 24 12 of of ADP cana-3756 24 13 learning learn VERB cana-3756 24 14 about about ADP cana-3756 24 15 complex complex ADJ cana-3756 24 16 patterns pattern NOUN cana-3756 24 17 with with ADP cana-3756 24 18 this this DET cana-3756 24 19 model model NOUN cana-3756 24 20 . . PUNCT cana-3756 25 1 most most ADV cana-3756 25 2 importantly importantly ADV cana-3756 25 3 , , PUNCT cana-3756 25 4 comparative comparative ADJ cana-3756 25 5 analysis analysis NOUN cana-3756 25 6 with with ADP cana-3756 25 7 state state NOUN cana-3756 25 8 - - PUNCT cana-3756 25 9 of of ADP cana-3756 25 10 - - PUNCT cana-3756 25 11 the the DET cana-3756 25 12 - - PUNCT cana-3756 25 13 art art NOUN cana-3756 25 14 methodologies methodology NOUN cana-3756 25 15 to to ADP cana-3756 25 16 that that DET cana-3756 25 17 end end NOUN cana-3756 25 18 shows show VERB cana-3756 25 19 our our PRON cana-3756 25 20 proposed propose VERB cana-3756 25 21 models model NOUN cana-3756 25 22 superior superior ADJ cana-3756 25 23 to to ADP cana-3756 25 24 other other ADJ cana-3756 25 25 models model NOUN cana-3756 25 26 of of ADP cana-3756 25 27 the the DET cana-3756 25 28 kind kind NOUN cana-3756 25 29 in in ADP cana-3756 25 30 terms term NOUN cana-3756 25 31 of of ADP cana-3756 25 32 both both PRON cana-3756 25 33 accuracy accuracy NOUN cana-3756 25 34 and and CCONJ cana-3756 25 35 computational computational ADJ cana-3756 25 36 efficiency efficiency NOUN cana-3756 25 37 . . PUNCT cana-3756 26 1 even even ADV cana-3756 26 2 traditional traditional ADJ cana-3756 26 3 deep deep ADJ cana-3756 26 4 learning learning NOUN cana-3756 26 5 models model NOUN cana-3756 26 6 normally normally ADV cana-3756 26 7 come come VERB cana-3756 26 8 with with ADP cana-3756 26 9 some some DET cana-3756 26 10 trade trade NOUN cana-3756 26 11 - - PUNCT cana-3756 26 12 off off NOUN cana-3756 26 13 between between ADP cana-3756 26 14 performance performance NOUN cana-3756 26 15 and and CCONJ cana-3756 26 16 resource resource NOUN cana-3756 26 17 utilization utilization NOUN cana-3756 26 18 . . PUNCT cana-3756 27 1 our our PRON cana-3756 27 2 accuracy accuracy NOUN cana-3756 27 3 is be AUX cana-3756 27 4 96.73 96.73 NUM cana-3756 27 5 % % NOUN cana-3756 27 6 , , PUNCT cana-3756 27 7 which which PRON cana-3756 27 8 surpasses surpass VERB cana-3756 27 9 many many ADJ cana-3756 27 10 of of ADP cana-3756 27 11 the the DET cana-3756 27 12 traditional traditional ADJ cana-3756 27 13 approaches approach NOUN cana-3756 27 14 , , PUNCT cana-3756 27 15 yet yet CCONJ cana-3756 27 16 it it PRON cana-3756 27 17 is be AUX cana-3756 27 18 not not PART cana-3756 27 19 too too ADV cana-3756 27 20 large large ADJ cana-3756 27 21 in in ADP cana-3756 27 22 terms term NOUN cana-3756 27 23 of of ADP cana-3756 27 24 parameters parameter NOUN cana-3756 27 25 and and CCONJ cana-3756 27 26 has have AUX cana-3756 27 27 not not PART cana-3756 27 28 incurred incur VERB cana-3756 27 29 heavy heavy ADJ cana-3756 27 30 computational computational ADJ cana-3756 27 31 overhead overhead NOUN cana-3756 27 32 . . PUNCT cana-3756 28 1 in in ADP cana-3756 28 2 addition addition NOUN cana-3756 28 3 , , PUNCT cana-3756 28 4 our our PRON cana-3756 28 5 architectures architecture NOUN cana-3756 28 6 - - PUNCT cana-3756 28 7 mobilenetv2 mobilenetv2 NOUN cana-3756 28 8 - - PUNCT cana-3756 28 9 lstm lstm PROPN cana-3756 28 10 and and CCONJ cana-3756 28 11 cnnlstm cnnlstm NOUN cana-3756 28 12 - - PUNCT cana-3756 28 13 achieved achieve VERB cana-3756 28 14 respective respective ADJ cana-3756 28 15 accuracies accuracy NOUN cana-3756 28 16 of of ADP cana-3756 28 17 80 80 NUM cana-3756 28 18 % % NOUN cana-3756 28 19 and and CCONJ cana-3756 28 20 85 85 NUM cana-3756 28 21 % % NOUN cana-3756 28 22 . . PUNCT cana-3756 29 1 extensive extensive ADJ cana-3756 29 2 experimental experimental ADJ cana-3756 29 3 validation validation NOUN cana-3756 29 4 on on ADP cana-3756 29 5 a a DET cana-3756 29 6 large large ADJ cana-3756 29 7 number number NOUN cana-3756 29 8 of of ADP cana-3756 29 9 diverse diverse ADJ cana-3756 29 10 benchmark benchmark NOUN cana-3756 29 11 datasets dataset NOUN cana-3756 29 12 is be AUX cana-3756 29 13 used use VERB cana-3756 29 14 to to PART cana-3756 29 15 ensure ensure VERB cana-3756 29 16 robustness robustness NOUN cana-3756 29 17 and and CCONJ cana-3756 29 18 generalizability generalizability NOUN cana-3756 29 19 . . PUNCT cana-3756 30 1 for for ADP cana-3756 30 2 the the DET cana-3756 30 3 real real ADJ cana-3756 30 4 - - PUNCT cana-3756 30 5 world world NOUN cana-3756 30 6 assessment assessment NOUN cana-3756 30 7 , , PUNCT cana-3756 30 8 the the DET cana-3756 30 9 proposed propose VERB cana-3756 30 10 models model NOUN cana-3756 30 11 are be AUX cana-3756 30 12 tested test VERB cana-3756 30 13 and and CCONJ cana-3756 30 14 evaluated evaluate VERB cana-3756 30 15 using use VERB cana-3756 30 16 multiple multiple ADJ cana-3756 30 17 performance performance NOUN cana-3756 30 18 metrics metric NOUN cana-3756 30 19 : : PUNCT cana-3756 30 20 accuracy accuracy NOUN cana-3756 30 21 , , PUNCT cana-3756 30 22 precision precision NOUN cana-3756 30 23 , , PUNCT cana-3756 30 24 recall recall NOUN cana-3756 30 25 , , PUNCT cana-3756 30 26 and and CCONJ cana-3756 30 27 inference inference NOUN cana-3756 30 28 speed speed NOUN cana-3756 30 29 . . PUNCT cana-3756 31 1 the the DET cana-3756 31 2 experiments experiment NOUN cana-3756 31 3 conducted conduct VERB cana-3756 31 4 indicate indicate VERB cana-3756 31 5 that that SCONJ cana-3756 31 6 the the DET cana-3756 31 7 model model NOUN cana-3756 31 8 based base VERB cana-3756 31 9 on on ADP cana-3756 31 10 efficientnetb2 efficientnetb2 X cana-3756 31 11 is be AUX cana-3756 31 12 especially especially ADV cana-3756 31 13 suitable suitable ADJ cana-3756 31 14 for for ADP cana-3756 31 15 the the DET cana-3756 31 16 real real ADJ cana-3756 31 17 - - PUNCT cana-3756 31 18 time time NOUN cana-3756 31 19 application application NOUN cana-3756 31 20 in in ADP cana-3756 31 21 which which PRON cana-3756 31 22 there there PRON cana-3756 31 23 has have VERB cana-3756 31 24 to to PART cana-3756 31 25 be be AUX cana-3756 31 26 a a DET cana-3756 31 27 compromise compromise NOUN cana-3756 31 28 between between ADP cana-3756 31 29 high high ADJ cana-3756 31 30 accuracy accuracy NOUN cana-3756 31 31 and and CCONJ cana-3756 31 32 computational computational ADJ cana-3756 31 33 efficiency efficiency NOUN cana-3756 31 34 . . PUNCT cana-3756 32 1 this this DET cana-3756 32 2 work work NOUN cana-3756 32 3 contributes contribute VERB cana-3756 32 4 to to ADP cana-3756 32 5 the the DET cana-3756 32 6 state state NOUN cana-3756 32 7 - - PUNCT cana-3756 32 8 of of ADP cana-3756 32 9 - - PUNCT cana-3756 32 10 the the DET cana-3756 32 11 - - PUNCT cana-3756 32 12 art art NOUN cana-3756 32 13 gender gender NOUN cana-3756 32 14 recognition recognition NOUN cana-3756 32 15 systems system NOUN cana-3756 32 16 by by ADP cana-3756 32 17 pointing point VERB cana-3756 32 18 out out ADP cana-3756 32 19 the the DET cana-3756 32 20 developments development NOUN cana-3756 32 21 that that PRON cana-3756 32 22 are be AUX cana-3756 32 23 particularly particularly ADV cana-3756 32 24 based base VERB cana-3756 32 25 on on ADP cana-3756 32 26 the the DET cana-3756 32 27 limitation limitation NOUN cana-3756 32 28 of of ADP cana-3756 32 29 existing exist VERB cana-3756 32 30 deep deep ADJ cana-3756 32 31 learning learning NOUN cana-3756 32 32 methods method NOUN cana-3756 32 33 and and CCONJ cana-3756 32 34 more more ADV cana-3756 32 35 efficient efficient ADJ cana-3756 32 36 architectures architecture NOUN cana-3756 32 37 that that PRON cana-3756 32 38 could could AUX cana-3756 32 39 be be AUX cana-3756 32 40 introduced introduce VERB cana-3756 32 41 for for ADP cana-3756 32 42 this this DET cana-3756 32 43 problem problem NOUN cana-3756 32 44 . . PUNCT cana-3756 33 1 literature literature NOUN cana-3756 33 2 review review NOUN cana-3756 33 3 with with ADP cana-3756 33 4 the the DET cana-3756 33 5 introduction introduction NOUN cana-3756 33 6 of of ADP cana-3756 33 7 deep deep ADJ cana-3756 33 8 learning learning NOUN cana-3756 33 9 architectures architecture NOUN cana-3756 33 10 , , PUNCT cana-3756 33 11 gender gender NOUN cana-3756 33 12 recognition recognition NOUN cana-3756 33 13 from from ADP cana-3756 33 14 facial facial ADJ cana-3756 33 15 photos photo NOUN cana-3756 33 16 has have AUX cana-3756 33 17 evolved evolve VERB cana-3756 33 18 enough enough ADV cana-3756 33 19 within within ADP cana-3756 33 20 the the DET cana-3756 33 21 discipline discipline NOUN cana-3756 33 22 . . PUNCT cana-3756 34 1 this this DET cana-3756 34 2 section section NOUN cana-3756 34 3 discusses discuss VERB cana-3756 34 4 in in ADP cana-3756 34 5 detail detail NOUN cana-3756 34 6 the the DET cana-3756 34 7 major major ADJ cana-3756 34 8 advancements advancement NOUN cana-3756 34 9 that that PRON cana-3756 34 10 have have AUX cana-3756 34 11 been be AUX cana-3756 34 12 made make VERB cana-3756 34 13 within within ADP cana-3756 34 14 the the DET cana-3756 34 15 discipline discipline NOUN cana-3756 34 16 over over ADP cana-3756 34 17 the the DET cana-3756 34 18 last last ADJ cana-3756 34 19 ten ten NUM cana-3756 34 20 years year NOUN cana-3756 34 21 . . PUNCT cana-3756 35 1 early early ADJ cana-3756 35 2 standards standard NOUN cana-3756 35 3 for for ADP cana-3756 35 4 deep deep ADJ cana-3756 35 5 learning learning NOUN cana-3756 35 6 in in ADP cana-3756 35 7 gender gender NOUN cana-3756 35 8 recognition recognition NOUN cana-3756 35 9 were be AUX cana-3756 35 10 provided provide VERB cana-3756 35 11 by by ADP cana-3756 35 12 levi levi PROPN cana-3756 35 13 and and CCONJ cana-3756 35 14 hassner hassner NOUN cana-3756 35 15 in in ADP cana-3756 35 16 their their PRON cana-3756 35 17 seminal seminal ADJ cana-3756 35 18 work work NOUN cana-3756 36 1 [ [ X cana-3756 36 2 1 1 X cana-3756 36 3 ] ] PUNCT cana-3756 36 4 that that PRON cana-3756 36 5 described describe VERB cana-3756 36 6 a a DET cana-3756 36 7 cnn cnn PROPN cana-3756 36 8 - - PUNCT cana-3756 36 9 based base VERB cana-3756 36 10 architecture architecture NOUN cana-3756 36 11 with with ADP cana-3756 36 12 86.8 86.8 NUM cana-3756 36 13 % % NOUN cana-3756 36 14 accuracy accuracy NOUN cana-3756 36 15 on on ADP cana-3756 36 16 the the DET cana-3756 36 17 adience adience NOUN cana-3756 36 18 dataset dataset NOUN cana-3756 36 19 . . PUNCT cana-3756 37 1 their their PRON cana-3756 37 2 approach approach NOUN cana-3756 37 3 had have VERB cana-3756 37 4 difficulties difficulty NOUN cana-3756 37 5 with with ADP cana-3756 37 6 extreme extreme ADJ cana-3756 37 7 position position NOUN cana-3756 37 8 variations variation NOUN cana-3756 37 9 , , PUNCT cana-3756 37 10 but but CCONJ cana-3756 37 11 demonstrated demonstrate VERB cana-3756 37 12 that that SCONJ cana-3756 37 13 deep deep ADJ cana-3756 37 14 neural neural ADJ cana-3756 37 15 networks network NOUN cana-3756 37 16 can can AUX cana-3756 37 17 indeed indeed ADV cana-3756 37 18 be be AUX cana-3756 37 19 applied apply VERB cana-3756 37 20 for for ADP cana-3756 37 21 this this DET cana-3756 37 22 task task NOUN cana-3756 37 23 . . PUNCT cana-3756 38 1 based base VERB cana-3756 38 2 on on ADP cana-3756 38 3 this this PRON cana-3756 38 4 , , PUNCT cana-3756 38 5 wang wang PROPN cana-3756 38 6 et et PROPN cana-3756 38 7 al al PROPN cana-3756 38 8 . . PUNCT cana-3756 39 1 [ [ X cana-3756 39 2 2 2 X cana-3756 39 3 ] ] PUNCT cana-3756 39 4 accomplished accomplish VERB cana-3756 39 5 the the DET cana-3756 39 6 task task NOUN cana-3756 39 7 with with ADP cana-3756 39 8 a a DET cana-3756 39 9 recognition recognition NOUN cana-3756 39 10 accuracy accuracy NOUN cana-3756 39 11 of of ADP cana-3756 39 12 89.2 89.2 NUM cana-3756 39 13 % % NOUN cana-3756 39 14 on on ADP cana-3756 39 15 gender gender NOUN cana-3756 39 16 through through ADP cana-3756 39 17 suggesting suggest VERB cana-3756 39 18 a a DET cana-3756 39 19 multi multi ADJ cana-3756 39 20 - - ADJ cana-3756 39 21 task task ADJ cana-3756 39 22 learning learn VERB cana-3756 39 23 architecture architecture NOUN cana-3756 39 24 , , PUNCT cana-3756 39 25 which which PRON cana-3756 39 26 involves involve VERB cana-3756 39 27 combining combine VERB cana-3756 39 28 age age NOUN cana-3756 39 29 estimation estimation NOUN cana-3756 39 30 and and CCONJ cana-3756 39 31 gender gender NOUN cana-3756 39 32 recognition recognition NOUN cana-3756 39 33 in in ADP cana-3756 39 34 a a DET cana-3756 39 35 singular singular ADJ cana-3756 39 36 process process NOUN cana-3756 39 37 . . PUNCT cana-3756 40 1 shared share VERB cana-3756 40 2 representation representation NOUN cana-3756 40 3 across across ADP cana-3756 40 4 related related ADJ cana-3756 40 5 activities activity NOUN cana-3756 40 6 were be AUX cana-3756 40 7 advantages advantage NOUN cana-3756 40 8 well well ADV cana-3756 40 9 explained explain VERB cana-3756 40 10 through through ADP cana-3756 40 11 their their PRON cana-3756 40 12 studies study NOUN cana-3756 40 13 . . PUNCT cana-3756 41 1 communications communication NOUN cana-3756 41 2 on on ADP cana-3756 41 3 applied apply VERB cana-3756 41 4 nonlinear nonlinear ADJ cana-3756 41 5 analysis analysis NOUN cana-3756 41 6 issn issn NOUN cana-3756 41 7 : : PUNCT cana-3756 41 8 1074 1074 NUM cana-3756 41 9 - - PUNCT cana-3756 41 10 133x 133x NUM cana-3756 41 11 vol vol NOUN cana-3756 41 12 32 32 NUM cana-3756 41 13 no no NOUN cana-3756 41 14 . . PUNCT cana-3756 42 1 8s 8s PROPN cana-3756 42 2 ( ( PUNCT cana-3756 42 3 2025 2025 NUM cana-3756 42 4 ) ) PUNCT cana-3756 42 5 687 687 NUM cana-3756 42 6 https://internationalpubls.com https://internationalpubls.com X cana-3756 42 7 when when SCONJ cana-3756 42 8 compared compare VERB cana-3756 42 9 to to ADP cana-3756 42 10 the the DET cana-3756 42 11 existing exist VERB cana-3756 42 12 models model NOUN cana-3756 42 13 , , PUNCT cana-3756 42 14 liu liu PROPN cana-3756 42 15 and and CCONJ cana-3756 42 16 zhang zhang PROPN cana-3756 42 17 's 's PART cana-3756 42 18 lightweight lightweight ADJ cana-3756 42 19 cnn cnn PROPN cana-3756 42 20 architecture architecture NOUN cana-3756 42 21 targeting target VERB cana-3756 42 22 mobile mobile ADJ cana-3756 42 23 devices device NOUN cana-3756 42 24 achieves achieve VERB cana-3756 42 25 87.4 87.4 NUM cana-3756 42 26 % % NOUN cana-3756 42 27 accuracy accuracy NOUN cana-3756 42 28 while while SCONJ cana-3756 42 29 reducing reduce VERB cana-3756 42 30 the the DET cana-3756 42 31 computational computational ADJ cana-3756 42 32 complexity complexity NOUN cana-3756 42 33 to to ADP cana-3756 42 34 60 60 NUM cana-3756 42 35 % % NOUN cana-3756 42 36 [ [ X cana-3756 42 37 3 3 NUM cana-3756 42 38 ] ] PUNCT cana-3756 42 39 . . PUNCT cana-3756 43 1 by by ADP cana-3756 43 2 using use VERB cana-3756 43 3 resnet-50 resnet-50 PROPN cana-3756 43 4 developed develop VERB cana-3756 43 5 by by ADP cana-3756 43 6 chen chen PROPN cana-3756 43 7 et et PROPN cana-3756 43 8 al al PROPN cana-3756 43 9 . . PUNCT cana-3756 44 1 [ [ X cana-3756 44 2 4 4 NUM cana-3756 44 3 ] ] PUNCT cana-3756 44 4 customized customized ADJ cana-3756 44 5 modifications modification NOUN cana-3756 44 6 , , PUNCT cana-3756 44 7 he he PRON cana-3756 44 8 could could AUX cana-3756 44 9 achieve achieve VERB cana-3756 44 10 tremendous tremendous ADJ cana-3756 44 11 gain gain NOUN cana-3756 44 12 with with ADP cana-3756 44 13 a a DET cana-3756 44 14 score score NOUN cana-3756 44 15 of of ADP cana-3756 44 16 91.3 91.3 NUM cana-3756 44 17 % % NOUN cana-3756 44 18 on on ADP cana-3756 44 19 celeba celeba PROPN cana-3756 44 20 datasets dataset NOUN cana-3756 44 21 , , PUNCT cana-3756 44 22 and and CCONJ cana-3756 44 23 deep deep ADJ cana-3756 44 24 residual residual ADJ cana-3756 44 25 networks network NOUN cana-3756 44 26 helped help VERB cana-3756 44 27 his his PRON cana-3756 44 28 research research NOUN cana-3756 44 29 how how SCONJ cana-3756 44 30 this this PRON cana-3756 44 31 is be AUX cana-3756 44 32 great great ADJ cana-3756 44 33 for for ADP cana-3756 44 34 feature feature NOUN cana-3756 44 35 extraction extraction NOUN cana-3756 44 36 . . PUNCT cana-3756 45 1 the the DET cana-3756 45 2 key key ADJ cana-3756 45 3 advantage advantage NOUN cana-3756 45 4 of of ADP cana-3756 45 5 yang yang PROPN cana-3756 45 6 et et PROPN cana-3756 45 7 al al PROPN cana-3756 45 8 . . PROPN cana-3756 45 9 's 's PART cana-3756 45 10 study study NOUN cana-3756 45 11 was be AUX cana-3756 45 12 that that SCONJ cana-3756 45 13 it it PRON cana-3756 45 14 was be AUX cana-3756 45 15 possible possible ADJ cana-3756 45 16 to to PART cana-3756 45 17 achieve achieve VERB cana-3756 45 18 90.1 90.1 NUM cana-3756 45 19 % % NOUN cana-3756 45 20 accuracy accuracy NOUN cana-3756 45 21 with with ADP cana-3756 45 22 relatively relatively ADV cana-3756 45 23 reduced reduced ADJ cana-3756 45 24 computing computing NOUN cana-3756 45 25 complexity complexity NOUN cana-3756 45 26 using use VERB cana-3756 45 27 the the DET cana-3756 45 28 shufflenet shufflenet NOUN cana-3756 45 29 design design NOUN cana-3756 46 1 [ [ X cana-3756 46 2 5 5 NUM cana-3756 46 3 ] ] PUNCT cana-3756 46 4 . . PUNCT cana-3756 47 1 optimization optimization NOUN cana-3756 47 2 of of ADP cana-3756 47 3 various various ADJ cana-3756 47 4 designs design NOUN cana-3756 47 5 and and CCONJ cana-3756 47 6 use use NOUN cana-3756 47 7 of of ADP cana-3756 47 8 data datum NOUN cana-3756 47 9 augmentation augmentation NOUN cana-3756 47 10 methods method NOUN cana-3756 47 11 allowed allow VERB cana-3756 47 12 azzopardi azzopardi NOUN cana-3756 47 13 et et PROPN cana-3756 47 14 al al PROPN cana-3756 47 15 . . PROPN cana-3756 48 1 to to PART cana-3756 48 2 design design VERB cana-3756 48 3 a a DET cana-3756 48 4 system system NOUN cana-3756 48 5 based base VERB cana-3756 48 6 on on ADP cana-3756 48 7 the the DET cana-3756 48 8 vgg16 vgg16 NOUN cana-3756 48 9 architecture architecture NOUN cana-3756 48 10 , , PUNCT cana-3756 48 11 with with ADP cana-3756 48 12 an an DET cana-3756 48 13 accuracy accuracy NOUN cana-3756 48 14 level level NOUN cana-3756 48 15 of of ADP cana-3756 48 16 92.5 92.5 NUM cana-3756 48 17 % % NOUN cana-3756 48 18 at at ADP cana-3756 48 19 the the DET cana-3756 48 20 expense expense NOUN cana-3756 48 21 of of ADP cana-3756 48 22 increased increase VERB cana-3756 48 23 demands demand NOUN cana-3756 48 24 on on ADP cana-3756 48 25 processing process VERB cana-3756 48 26 [ [ X cana-3756 48 27 6 6 NUM cana-3756 48 28 ] ] PUNCT cana-3756 48 29 . . PUNCT cana-3756 49 1 zhang zhang PROPN cana-3756 49 2 and and CCONJ cana-3756 49 3 liu liu PROPN cana-3756 50 1 [ [ X cana-3756 50 2 7 7 X cana-3756 50 3 ] ] PUNCT cana-3756 50 4 have have AUX cana-3756 50 5 developed develop VERB cana-3756 50 6 a a DET cana-3756 50 7 spatial spatial ADJ cana-3756 50 8 attention attention NOUN cana-3756 50 9 mechanism mechanism NOUN cana-3756 50 10 using use VERB cana-3756 50 11 resnet50 resnet50 NOUN cana-3756 50 12 that that PRON cana-3756 50 13 reached reach VERB cana-3756 50 14 an an DET cana-3756 50 15 accuracy accuracy NOUN cana-3756 50 16 of of ADP cana-3756 50 17 93.8 93.8 NUM cana-3756 50 18 % % NOUN cana-3756 50 19 on on ADP cana-3756 50 20 the the DET cana-3756 50 21 celeba celeba PROPN cana-3756 50 22 dataset dataset VERB cana-3756 50 23 . . PUNCT cana-3756 51 1 they they PRON cana-3756 51 2 focused focus VERB cana-3756 51 3 on on ADP cana-3756 51 4 various various ADJ cana-3756 51 5 facial facial ADJ cana-3756 51 6 characteristics characteristic NOUN cana-3756 51 7 in in ADP cana-3756 51 8 their their PRON cana-3756 51 9 design design NOUN cana-3756 51 10 . . PUNCT cana-3756 52 1 kumar kumar PROPN cana-3756 52 2 and and CCONJ cana-3756 52 3 patel patel PROPN cana-3756 53 1 [ [ X cana-3756 53 2 8 8 NUM cana-3756 53 3 ] ] PUNCT cana-3756 53 4 proposed propose VERB cana-3756 53 5 a a DET cana-3756 53 6 channel channel NOUN cana-3756 53 7 attention attention NOUN cana-3756 53 8 approach approach NOUN cana-3756 53 9 combined combine VERB cana-3756 53 10 with with ADP cana-3756 53 11 mobilenetv2 mobilenetv2 PROPN cana-3756 53 12 which which PRON cana-3756 53 13 reached reach VERB cana-3756 53 14 92.1 92.1 NUM cana-3756 53 15 % % NOUN cana-3756 53 16 accuracy accuracy NOUN cana-3756 53 17 with with ADP cana-3756 53 18 economical economical ADJ cana-3756 53 19 inference inference NOUN cana-3756 53 20 time time NOUN cana-3756 53 21 . . PUNCT cana-3756 54 1 singh singh PROPN cana-3756 54 2 et et PROPN cana-3756 54 3 al al PROPN cana-3756 54 4 . . PROPN cana-3756 54 5 used use VERB cana-3756 54 6 densenet121 densenet121 PROPN cana-3756 54 7 and and CCONJ cana-3756 54 8 transfer transfer VERB cana-3756 54 9 learning learning NOUN cana-3756 54 10 in in ADP cana-3756 54 11 addition addition NOUN cana-3756 54 12 to to ADP cana-3756 54 13 feature feature NOUN cana-3756 54 14 fusion fusion NOUN cana-3756 54 15 and and CCONJ cana-3756 54 16 data datum NOUN cana-3756 54 17 preprocessing preprocessing NOUN cana-3756 54 18 and and CCONJ cana-3756 54 19 achieved achieve VERB cana-3756 54 20 an an DET cana-3756 54 21 accuracy accuracy NOUN cana-3756 54 22 of of ADP cana-3756 54 23 94.2 94.2 NUM cana-3756 54 24 % % NOUN cana-3756 55 1 [ [ X cana-3756 55 2 9 9 NUM cana-3756 55 3 ] ] PUNCT cana-3756 55 4 . . PUNCT cana-3756 56 1 park park NOUN cana-3756 56 2 et et PROPN cana-3756 56 3 al al PROPN cana-3756 56 4 . . PUNCT cana-3756 57 1 [ [ X cana-3756 57 2 10 10 NUM cana-3756 57 3 ] ] PUNCT cana-3756 57 4 have have AUX cana-3756 57 5 exhibited exhibit VERB cana-3756 57 6 the the DET cana-3756 57 7 ability ability NOUN cana-3756 57 8 of of ADP cana-3756 57 9 hybrid hybrid ADJ cana-3756 57 10 architectures architecture NOUN cana-3756 57 11 by by ADP cana-3756 57 12 combining combine VERB cana-3756 57 13 cnn cnn PROPN cana-3756 57 14 and and CCONJ cana-3756 57 15 transformer transformer NOUN cana-3756 57 16 encoders encoder NOUN cana-3756 57 17 achieving achieve VERB cana-3756 57 18 93.7 93.7 NUM cana-3756 57 19 % % NOUN cana-3756 57 20 accuracy accuracy NOUN cana-3756 57 21 . . PUNCT cana-3756 58 1 chen chen PROPN cana-3756 58 2 and and CCONJ cana-3756 58 3 wang wang PROPN cana-3756 59 1 [ [ X cana-3756 59 2 11 11 NUM cana-3756 59 3 ] ] PUNCT cana-3756 59 4 have have AUX cana-3756 59 5 created create VERB cana-3756 59 6 a a DET cana-3756 59 7 lightweight lightweight ADJ cana-3756 59 8 architecture architecture NOUN cana-3756 59 9 based base VERB cana-3756 59 10 on on ADP cana-3756 59 11 mobilenetv3 mobilenetv3 PROPN cana-3756 59 12 achieving achieve VERB cana-3756 59 13 91.3 91.3 NUM cana-3756 59 14 % % NOUN cana-3756 59 15 accuracy accuracy NOUN cana-3756 59 16 with with ADP cana-3756 59 17 a a DET cana-3756 59 18 much much ADV cana-3756 59 19 lower low ADJ cana-3756 59 20 count count NOUN cana-3756 59 21 of of ADP cana-3756 59 22 parameters parameter NOUN cana-3756 59 23 . . PUNCT cana-3756 60 1 a a DET cana-3756 60 2 cnn cnn PROPN cana-3756 60 3 - - PUNCT cana-3756 60 4 rnn rnn VERB cana-3756 60 5 hybrid hybrid ADJ cana-3756 60 6 architecture architecture NOUN cana-3756 60 7 has have AUX cana-3756 60 8 been be AUX cana-3756 60 9 presented present VERB cana-3756 60 10 by by ADP cana-3756 60 11 kumar kumar PROPN cana-3756 60 12 et et PROPN cana-3756 60 13 al al PROPN cana-3756 60 14 . . PUNCT cana-3756 61 1 [ [ X cana-3756 61 2 12 12 NUM cana-3756 61 3 ] ] PUNCT cana-3756 61 4 , , PUNCT cana-3756 61 5 and and CCONJ cana-3756 61 6 some some DET cana-3756 61 7 features feature NOUN cana-3756 61 8 have have AUX cana-3756 61 9 been be AUX cana-3756 61 10 captured capture VERB cana-3756 61 11 in in ADP cana-3756 61 12 facial facial ADJ cana-3756 61 13 sequences sequence NOUN cana-3756 61 14 with with ADP cana-3756 61 15 an an DET cana-3756 61 16 accuracy accuracy NOUN cana-3756 61 17 of of ADP cana-3756 61 18 88.7 88.7 NUM cana-3756 61 19 % % NOUN cana-3756 61 20 . . PUNCT cana-3756 62 1 li li PROPN cana-3756 62 2 et et PROPN cana-3756 62 3 al al PROPN cana-3756 62 4 . . PUNCT cana-3756 63 1 [ [ X cana-3756 63 2 13 13 NUM cana-3756 63 3 ] ] PUNCT cana-3756 63 4 presented present VERB cana-3756 63 5 a a DET cana-3756 63 6 transformer transformer NOUN cana-3756 63 7 - - PUNCT cana-3756 63 8 based base VERB cana-3756 63 9 approach approach NOUN cana-3756 63 10 which which PRON cana-3756 63 11 yielded yield VERB cana-3756 63 12 95.1 95.1 NUM cana-3756 63 13 % % NOUN cana-3756 63 14 accuracy accuracy NOUN cana-3756 63 15 , , PUNCT cana-3756 63 16 thus thus ADV cana-3756 63 17 establishing establish VERB cana-3756 63 18 new new ADJ cana-3756 63 19 state state NOUN cana-3756 63 20 - - PUNCT cana-3756 63 21 of of ADP cana-3756 63 22 - - PUNCT cana-3756 63 23 the the DET cana-3756 63 24 - - PUNCT cana-3756 63 25 art art NOUN cana-3756 63 26 for for ADP cana-3756 63 27 attention attention NOUN cana-3756 63 28 - - PUNCT cana-3756 63 29 based base VERB cana-3756 63 30 architectures architecture NOUN cana-3756 63 31 . . PUNCT cana-3756 64 1 park park NOUN cana-3756 64 2 and and CCONJ cana-3756 64 3 kim kim PROPN cana-3756 65 1 [ [ X cana-3756 65 2 14 14 NUM cana-3756 65 3 ] ] PUNCT cana-3756 65 4 proposed propose VERB cana-3756 65 5 an an DET cana-3756 65 6 efficientnetb0based efficientnetb0base VERB cana-3756 65 7 system system NOUN cana-3756 65 8 that that PRON cana-3756 65 9 has have AUX cana-3756 65 10 attained attain VERB cana-3756 65 11 an an DET cana-3756 65 12 accuracy accuracy NOUN cana-3756 65 13 of of ADP cana-3756 65 14 93.4 93.4 NUM cana-3756 65 15 % % NOUN cana-3756 65 16 while while SCONJ cana-3756 65 17 optimizing optimize VERB cana-3756 65 18 inference inference NOUN cana-3756 65 19 time time NOUN cana-3756 65 20 . . PUNCT cana-3756 66 1 rodriguez rodriguez NOUN cana-3756 66 2 et et PROPN cana-3756 66 3 al al PROPN cana-3756 66 4 . . PUNCT cana-3756 67 1 [ [ X cana-3756 67 2 15 15 NUM cana-3756 67 3 ] ] PUNCT cana-3756 67 4 proposed propose VERB cana-3756 67 5 a a DET cana-3756 67 6 multi multi ADJ cana-3756 67 7 - - ADJ cana-3756 67 8 task task ADJ cana-3756 67 9 learning learning NOUN cana-3756 67 10 - - PUNCT cana-3756 67 11 based base VERB cana-3756 67 12 approach approach NOUN cana-3756 67 13 that that PRON cana-3756 67 14 has have AUX cana-3756 67 15 reached reach VERB cana-3756 67 16 an an DET cana-3756 67 17 accuracy accuracy NOUN cana-3756 67 18 of of ADP cana-3756 67 19 94.8 94.8 NUM cana-3756 67 20 % % NOUN cana-3756 67 21 while while SCONJ cana-3756 67 22 simultaneously simultaneously ADV cana-3756 67 23 estimating estimate VERB cana-3756 67 24 the the DET cana-3756 67 25 age age NOUN cana-3756 67 26 . . PUNCT cana-3756 68 1 thompson thompson PROPN cana-3756 68 2 et et PROPN cana-3756 68 3 al al PROPN cana-3756 68 4 . . PUNCT cana-3756 69 1 [ [ X cana-3756 69 2 16 16 NUM cana-3756 69 3 ] ] PUNCT cana-3756 69 4 present present ADJ cana-3756 69 5 a a DET cana-3756 69 6 lightweight lightweight ADJ cana-3756 69 7 version version NOUN cana-3756 69 8 of of ADP cana-3756 69 9 efficientnetv2 efficientnetv2 NOUN cana-3756 69 10 achieving achieve VERB cana-3756 69 11 94.5 94.5 NUM cana-3756 69 12 % % NOUN cana-3756 69 13 with with ADP cana-3756 69 14 minimal minimal ADJ cana-3756 69 15 computational computational ADJ cana-3756 69 16 overhead overhead NOUN cana-3756 69 17 . . PUNCT cana-3756 70 1 martinez martinez PROPN cana-3756 70 2 and and CCONJ cana-3756 70 3 garcia garcia PROPN cana-3756 71 1 [ [ X cana-3756 71 2 17 17 NUM cana-3756 71 3 ] ] PUNCT cana-3756 71 4 suggest suggest VERB cana-3756 71 5 an an DET cana-3756 71 6 innovative innovative ADJ cana-3756 71 7 feature feature NOUN cana-3756 71 8 fusion fusion NOUN cana-3756 71 9 technique technique NOUN cana-3756 71 10 by by ADP cana-3756 71 11 amalgamating amalgamate VERB cana-3756 71 12 the the DET cana-3756 71 13 global global ADJ cana-3756 71 14 and and CCONJ cana-3756 71 15 local local ADJ cana-3756 71 16 facial facial ADJ cana-3756 71 17 features feature NOUN cana-3756 71 18 which which PRON cana-3756 71 19 achieves achieve VERB cana-3756 71 20 93.9 93.9 NUM cana-3756 71 21 % % NOUN cana-3756 71 22 accuracy accuracy NOUN cana-3756 71 23 . . PUNCT cana-3756 72 1 wilson wilson PROPN cana-3756 72 2 et et PROPN cana-3756 72 3 al al PROPN cana-3756 72 4 . . PUNCT cana-3756 73 1 [ [ X cana-3756 73 2 18 18 NUM cana-3756 73 3 ] ] PUNCT cana-3756 73 4 use use VERB cana-3756 73 5 ensemble ensemble ADJ cana-3756 73 6 learning learning NOUN cana-3756 73 7 with with ADP cana-3756 73 8 multiple multiple ADJ cana-3756 73 9 light light ADJ cana-3756 73 10 - - PUNCT cana-3756 73 11 weight weight NOUN cana-3756 73 12 models model NOUN cana-3756 73 13 . . PUNCT cana-3756 74 1 it it PRON cana-3756 74 2 has have AUX cana-3756 74 3 reported report VERB cana-3756 74 4 95.3 95.3 NUM cana-3756 74 5 % % NOUN cana-3756 74 6 while while SCONJ cana-3756 74 7 having have VERB cana-3756 74 8 a a DET cana-3756 74 9 tolerable tolerable ADJ cana-3756 74 10 inference inference NOUN cana-3756 74 11 time time NOUN cana-3756 74 12 . . PUNCT cana-3756 75 1 zhao zhao PROPN cana-3756 75 2 et et PROPN cana-3756 75 3 al al PROPN cana-3756 75 4 . . PUNCT cana-3756 76 1 [ [ X cana-3756 76 2 19 19 NUM cana-3756 76 3 ] ] PUNCT cana-3756 76 4 applied apply VERB cana-3756 76 5 self self NOUN cana-3756 76 6 - - PUNCT cana-3756 76 7 attention attention NOUN cana-3756 76 8 with with ADP cana-3756 76 9 mobilenetv3 mobilenetv3 PROPN cana-3756 76 10 , , PUNCT cana-3756 76 11 obtaining obtain VERB cana-3756 76 12 92.8 92.8 NUM cana-3756 76 13 % % NOUN cana-3756 76 14 accuracy accuracy NOUN cana-3756 76 15 with with ADP cana-3756 76 16 improvements improvement NOUN cana-3756 76 17 in in ADP cana-3756 76 18 robustness robustness NOUN cana-3756 76 19 to to PART cana-3756 76 20 pose pose VERB cana-3756 76 21 variations variation NOUN cana-3756 76 22 . . PUNCT cana-3756 77 1 kim kim PROPN cana-3756 77 2 and and CCONJ cana-3756 77 3 lee lee PROPN cana-3756 78 1 [ [ X cana-3756 78 2 20 20 NUM cana-3756 78 3 ] ] PUNCT cana-3756 78 4 proposed propose VERB cana-3756 78 5 a a DET cana-3756 78 6 hybrid hybrid ADJ cana-3756 78 7 architecture architecture NOUN cana-3756 78 8 by by ADP cana-3756 78 9 adding add VERB cana-3756 78 10 transformer transformer NOUN cana-3756 78 11 blocks block NOUN cana-3756 78 12 on on ADP cana-3756 78 13 top top NOUN cana-3756 78 14 of of ADP cana-3756 78 15 efficientnet efficientnet NOUN cana-3756 78 16 and and CCONJ cana-3756 78 17 achieving achieve VERB cana-3756 78 18 an an DET cana-3756 78 19 accuracy accuracy NOUN cana-3756 78 20 of of ADP cana-3756 78 21 95.7 95.7 NUM cana-3756 78 22 % % NOUN cana-3756 78 23 . . PUNCT cana-3756 79 1 proposed propose VERB cana-3756 79 2 system system NOUN cana-3756 79 3 we we PRON cana-3756 79 4 propose propose VERB cana-3756 79 5 three three NUM cana-3756 79 6 distinct distinct ADJ cana-3756 79 7 deep deep ADJ cana-3756 79 8 learning learning NOUN cana-3756 79 9 architectures architecture NOUN cana-3756 79 10 for for ADP cana-3756 79 11 gender gender NOUN cana-3756 79 12 recognition recognition NOUN cana-3756 79 13 , , PUNCT cana-3756 79 14 each each DET cana-3756 79 15 one one NOUN cana-3756 79 16 is be AUX cana-3756 79 17 designed design VERB cana-3756 79 18 to to PART cana-3756 79 19 balance balance VERB cana-3756 79 20 accuracy accuracy NOUN cana-3756 79 21 , , PUNCT cana-3756 79 22 computational computational ADJ cana-3756 79 23 efficiency efficiency NOUN cana-3756 79 24 , , PUNCT cana-3756 79 25 and and CCONJ cana-3756 79 26 real real ADJ cana-3756 79 27 - - PUNCT cana-3756 79 28 world world NOUN cana-3756 79 29 applicability applicability NOUN cana-3756 79 30 . . PUNCT cana-3756 80 1 illustrates illustrate VERB cana-3756 80 2 the the DET cana-3756 80 3 high high ADJ cana-3756 80 4 - - PUNCT cana-3756 80 5 level level NOUN cana-3756 80 6 architecture architecture NOUN cana-3756 80 7 of of ADP cana-3756 80 8 our our PRON cana-3756 80 9 proposed propose VERB cana-3756 80 10 models model NOUN cana-3756 80 11 . . PUNCT cana-3756 81 1 communications communication NOUN cana-3756 81 2 on on ADP cana-3756 81 3 applied apply VERB cana-3756 81 4 nonlinear nonlinear ADJ cana-3756 81 5 analysis analysis NOUN cana-3756 81 6 issn issn NOUN cana-3756 81 7 : : PUNCT cana-3756 81 8 1074 1074 NUM cana-3756 81 9 - - PUNCT cana-3756 81 10 133x 133x NUM cana-3756 81 11 vol vol NOUN cana-3756 81 12 32 32 NUM cana-3756 81 13 no no NOUN cana-3756 81 14 . . PUNCT cana-3756 82 1 8s 8s PROPN cana-3756 82 2 ( ( PUNCT cana-3756 82 3 2025 2025 NUM cana-3756 82 4 ) ) PUNCT cana-3756 82 5 688 688 NUM cana-3756 83 1 https://internationalpubls.com https://internationalpubls.com X cana-3756 83 2 efficientnetb2 efficientnetb2 X cana-3756 84 1 with with ADP cana-3756 84 2 custom custom NOUN cana-3756 84 3 classifier classifier NOUN cana-3756 84 4 the the DET cana-3756 84 5 primary primary ADJ cana-3756 84 6 proposed propose VERB cana-3756 84 7 model model NOUN cana-3756 84 8 utilizes utilize VERB cana-3756 84 9 efficientnetb2 efficientnetb2 X cana-3756 84 10 as as ADP cana-3756 84 11 the the DET cana-3756 84 12 backbone backbone NOUN cana-3756 84 13 network network NOUN cana-3756 84 14 , , PUNCT cana-3756 84 15 enhanced enhance VERB cana-3756 84 16 with with ADP cana-3756 84 17 a a DET cana-3756 84 18 custom custom NOUN cana-3756 84 19 classifier classifier NOUN cana-3756 84 20 . . PUNCT cana-3756 85 1 the the DET cana-3756 85 2 architecture architecture NOUN cana-3756 85 3 consists consist VERB cana-3756 85 4 of of ADP cana-3756 85 5 : : PUNCT cana-3756 85 6 feature feature NOUN cana-3756 85 7 extraction extraction NOUN cana-3756 85 8 : : PUNCT cana-3756 85 9 the the DET cana-3756 85 10 proposed propose VERB cana-3756 85 11 model model NOUN cana-3756 85 12 is be AUX cana-3756 85 13 based base VERB cana-3756 85 14 on on ADP cana-3756 85 15 the the DET cana-3756 85 16 efficientnetb2 efficientnetb2 NOUN cana-3756 85 17 architecture architecture NOUN cana-3756 85 18 . . PUNCT cana-3756 86 1 in in ADP cana-3756 86 2 order order NOUN cana-3756 86 3 to to PART cana-3756 86 4 construct construct VERB cana-3756 86 5 such such ADJ cana-3756 86 6 , , PUNCT cana-3756 86 7 the the DET cana-3756 86 8 backbone backbone NOUN cana-3756 86 9 pre pre VERB cana-3756 86 10 - - VERB cana-3756 86 11 trained train VERB cana-3756 86 12 on on ADP cana-3756 86 13 imagenet imagenet NOUN cana-3756 86 14 should should AUX cana-3756 86 15 provide provide VERB cana-3756 86 16 robust robust ADJ cana-3756 86 17 feature feature NOUN cana-3756 86 18 extraction extraction NOUN cana-3756 86 19 . . PUNCT cana-3756 87 1 compound compound NOUN cana-3756 87 2 scaling scaling NOUN cana-3756 87 3 with with ADP cana-3756 87 4 a a DET cana-3756 87 5 coefficient coefficient NOUN cana-3756 87 6 of of ADP cana-3756 87 7 Ο† Ο† PROPN cana-3756 87 8 = = SYM cana-3756 87 9 0.3 0.3 NUM cana-3756 87 10 is be AUX cana-3756 87 11 adopted adopt VERB cana-3756 87 12 to to PART cana-3756 87 13 ensure ensure VERB cana-3756 87 14 that that SCONJ cana-3756 87 15 network network NOUN cana-3756 87 16 depth depth NOUN cana-3756 87 17 and and CCONJ cana-3756 87 18 width width VERB cana-3756 87 19 as as ADV cana-3756 87 20 well well ADV cana-3756 87 21 as as ADP cana-3756 87 22 the the DET cana-3756 87 23 input input NOUN cana-3756 87 24 resolution resolution NOUN cana-3756 87 25 increase increase VERB cana-3756 87 26 uniformly uniformly ADV cana-3756 87 27 . . PUNCT cana-3756 88 1 the the DET cana-3756 88 2 depth depth NOUN cana-3756 88 3 of of ADP cana-3756 88 4 the the DET cana-3756 88 5 network network NOUN cana-3756 88 6 is be AUX cana-3756 88 7 set set VERB cana-3756 88 8 to to ADP cana-3756 88 9 d d PROPN cana-3756 88 10 = = SYM cana-3756 88 11 3.1 3.1 NUM cana-3756 88 12 , , PUNCT cana-3756 88 13 which which PRON cana-3756 88 14 provides provide VERB cana-3756 88 15 an an DET cana-3756 88 16 adequate adequate ADJ cana-3756 88 17 number number NOUN cana-3756 88 18 of of ADP cana-3756 88 19 layers layer NOUN cana-3756 88 20 to to PART cana-3756 88 21 achieve achieve VERB cana-3756 88 22 hierarchical hierarchical ADJ cana-3756 88 23 feature feature NOUN cana-3756 88 24 learning learning NOUN cana-3756 88 25 . . PUNCT cana-3756 89 1 the the DET cana-3756 89 2 width width NOUN cana-3756 89 3 is be AUX cana-3756 89 4 dilated dilate VERB cana-3756 89 5 to to ADP cana-3756 89 6 w w NOUN cana-3756 89 7 = = NOUN cana-3756 89 8 1.1 1.1 NUM cana-3756 89 9 , , PUNCT cana-3756 89 10 and and CCONJ cana-3756 89 11 this this PRON cana-3756 89 12 improves improve VERB cana-3756 89 13 the the DET cana-3756 89 14 capacity capacity NOUN cana-3756 89 15 of of ADP cana-3756 89 16 the the DET cana-3756 89 17 network network NOUN cana-3756 89 18 keeping keep VERB cana-3756 89 19 efficiency efficiency NOUN cana-3756 89 20 ; ; PUNCT cana-3756 89 21 and and CCONJ cana-3756 89 22 moreover moreover ADV cana-3756 89 23 , , PUNCT cana-3756 89 24 input input NOUN cana-3756 89 25 r r NOUN cana-3756 89 26 = = SYM cana-3756 89 27 260 260 NUM cana-3756 89 28 allows allow VERB cana-3756 89 29 for for ADP cana-3756 89 30 resolution resolution NOUN cana-3756 89 31 where where SCONJ cana-3756 89 32 it it PRON cana-3756 89 33 becomes become VERB cana-3756 89 34 capable capable ADJ cana-3756 89 35 of of ADP cana-3756 89 36 processing process VERB cana-3756 89 37 the the DET cana-3756 89 38 facial facial ADJ cana-3756 89 39 nuances nuance NOUN cana-3756 89 40 better well ADV cana-3756 89 41 , , PUNCT cana-3756 89 42 raising raise VERB cana-3756 89 43 the the DET cana-3756 89 44 precision precision NOUN cana-3756 89 45 at at ADP cana-3756 89 46 the the DET cana-3756 89 47 classification classification NOUN cana-3756 89 48 end end NOUN cana-3756 89 49 for for ADP cana-3756 89 50 gender gender NOUN cana-3756 89 51 results result NOUN cana-3756 89 52 . . PUNCT cana-3756 90 1 𝑑 𝑑 NOUN cana-3756 90 2 = = X cana-3756 91 1 π›Όπœ‘ π›Όπœ‘ NOUN cana-3756 91 2 𝑀 𝑀 NOUN cana-3756 91 3 = = PRON cana-3756 91 4 π›½πœ‘ π›½πœ‘ NOUN cana-3756 91 5 π‘Ÿ π‘Ÿ NOUN cana-3756 91 6 = = PUNCT cana-3756 92 1 𝛾^πœ‘ 𝛾^πœ‘ PROPN cana-3756 92 2 where where SCONJ cana-3756 92 3 Ξ± Ξ± X cana-3756 92 4 , , PUNCT cana-3756 92 5 Ξ² Ξ² X cana-3756 92 6 , , PUNCT cana-3756 92 7 Ξ³ Ξ³ PROPN cana-3756 92 8 are be AUX cana-3756 92 9 architecture architecture NOUN cana-3756 92 10 - - PUNCT cana-3756 92 11 specific specific ADJ cana-3756 92 12 constants constant NOUN cana-3756 92 13 determined determine VERB cana-3756 92 14 through through ADP cana-3756 92 15 grid grid NOUN cana-3756 92 16 search search NOUN cana-3756 92 17 . . PUNCT cana-3756 93 1 custom custom NOUN cana-3756 93 2 classification classification NOUN cana-3756 93 3 head head NOUN cana-3756 93 4 : : PUNCT cana-3756 93 5 in in ADP cana-3756 93 6 order order NOUN cana-3756 93 7 to to PART cana-3756 93 8 avoid avoid VERB cana-3756 93 9 overfitting overfitte VERB cana-3756 93 10 , , PUNCT cana-3756 93 11 the the DET cana-3756 93 12 custom custom NOUN cana-3756 93 13 head head NOUN cana-3756 93 14 of of ADP cana-3756 93 15 the the DET cana-3756 93 16 classification classification NOUN cana-3756 93 17 in in ADP cana-3756 93 18 our our PRON cana-3756 93 19 study study NOUN cana-3756 93 20 consists consist VERB cana-3756 93 21 of of ADP cana-3756 93 22 global global ADJ cana-3756 93 23 average average ADJ cana-3756 93 24 pooling pooling NOUN cana-3756 93 25 , , PUNCT cana-3756 93 26 dropout dropout NOUN cana-3756 93 27 at at ADP cana-3756 93 28 0.4 0.4 NUM cana-3756 93 29 , , PUNCT cana-3756 93 30 followed follow VERB cana-3756 93 31 by by ADP cana-3756 93 32 a a DET cana-3756 93 33 dense dense ADJ cana-3756 93 34 layer layer NOUN cana-3756 93 35 with with ADP cana-3756 93 36 512 512 NUM cana-3756 93 37 units unit NOUN cana-3756 93 38 and and CCONJ cana-3756 93 39 relu relu NOUN cana-3756 93 40 activation activation NOUN cana-3756 93 41 after after ADP cana-3756 93 42 it it PRON cana-3756 93 43 , , PUNCT cana-3756 93 44 and and CCONJ cana-3756 93 45 stable stable ADJ cana-3756 93 46 training training NOUN cana-3756 93 47 can can AUX cana-3756 93 48 be be AUX cana-3756 93 49 reached reach VERB cana-3756 93 50 using use VERB cana-3756 93 51 batch batch NOUN cana-3756 93 52 normalization normalization NOUN cana-3756 93 53 , , PUNCT cana-3756 93 54 and and CCONJ cana-3756 93 55 finally finally ADV cana-3756 93 56 a a DET cana-3756 93 57 dense dense ADJ cana-3756 93 58 layer layer NOUN cana-3756 93 59 with with ADP cana-3756 93 60 two two NUM cana-3756 93 61 units unit NOUN cana-3756 93 62 , , PUNCT cana-3756 93 63 softmax softmax NOUN cana-3756 93 64 activation activation NOUN cana-3756 93 65 for for ADP cana-3756 93 66 gender gender NOUN cana-3756 93 67 classification classification NOUN cana-3756 93 68 . . PUNCT cana-3756 94 1 𝐹𝑙 𝐹𝑙 PROPN cana-3756 94 2 = = SYM cana-3756 94 3 𝐻𝑙(πΉπ‘™βˆ’1 𝐻𝑙(πΉπ‘™βˆ’1 PROPN cana-3756 94 4 ) ) PUNCT cana-3756 95 1 = = PUNCT cana-3756 95 2 𝜎(𝐡𝑁(π‘Šπ‘™ 𝜎(𝐡𝑁(π‘Šπ‘™ VERB cana-3756 95 3 βˆ— βˆ— NOUN cana-3756 95 4 πΉπ‘™βˆ’1 πΉπ‘™βˆ’1 NUM cana-3756 95 5 + + CCONJ cana-3756 95 6 𝑏𝑙 𝑏𝑙 PROPN cana-3756 95 7 ) ) PUNCT cana-3756 95 8 ) ) PUNCT cana-3756 96 1 where where SCONJ cana-3756 96 2 : : PUNCT cana-3756 96 3 𝐹𝑙 𝐹𝑙 PROPN cana-3756 96 4 π‘Ÿπ‘’π‘π‘Ÿπ‘’π‘ π‘’π‘›π‘‘π‘  π‘Ÿπ‘’π‘π‘Ÿπ‘’π‘ π‘’π‘›π‘‘π‘  NOUN cana-3756 96 5 π‘“π‘’π‘Žπ‘‘π‘’π‘Ÿπ‘’π‘  π‘“π‘’π‘Žπ‘‘π‘’π‘Ÿπ‘’π‘  VERB cana-3756 96 6 π‘Žπ‘‘ π‘Žπ‘‘ ADP cana-3756 96 7 π‘™π‘Žπ‘¦π‘’π‘Ÿ π‘™π‘Žπ‘¦π‘’π‘Ÿ ADJ cana-3756 96 8 𝑙 𝑙 PRON cana-3756 96 9 𝐻1 𝐻1 PROPN cana-3756 96 10 𝑖𝑠 𝑖𝑠 CCONJ cana-3756 96 11 π‘‘β„Žπ‘’ π‘‘β„Žπ‘’ VERB cana-3756 96 12 π‘‘π‘Ÿπ‘Žπ‘›π‘ π‘“π‘œπ‘Ÿπ‘šπ‘Žπ‘‘π‘–π‘œπ‘› π‘‘π‘Ÿπ‘Žπ‘›π‘ π‘“π‘œπ‘Ÿπ‘šπ‘Žπ‘‘π‘–π‘œπ‘› NOUN cana-3756 96 13 π‘“π‘’π‘›π‘π‘‘π‘–π‘œπ‘› π‘“π‘’π‘›π‘π‘‘π‘–π‘œπ‘› ADP cana-3756 96 14 𝜎 𝜎 PROPN cana-3756 97 1 𝑖𝑠 𝑖𝑠 NOUN cana-3756 97 2 π‘‘β„Žπ‘’ π‘‘β„Žπ‘’ ADJ cana-3756 97 3 π‘…π‘’πΏπ‘ˆ π‘…π‘’πΏπ‘ˆ PROPN cana-3756 97 4 π‘Žπ‘π‘‘π‘–π‘£π‘Žπ‘‘π‘–π‘œπ‘› π‘Žπ‘π‘‘π‘–π‘£π‘Žπ‘‘π‘–π‘œπ‘› ADJ cana-3756 97 5 bn bn NOUN cana-3756 97 6 denotes denote NOUN cana-3756 97 7 batch batch VERB cana-3756 97 8 normalization normalization NOUN cana-3756 97 9 π‘Šπ‘™ π‘Šπ‘™ ADP cana-3756 97 10 π‘Žπ‘›π‘‘ π‘Žπ‘›π‘‘ ADJ cana-3756 97 11 𝑏𝑙 𝑏𝑙 PROPN cana-3756 97 12 π‘Žπ‘Ÿπ‘’ π‘Žπ‘Ÿπ‘’ PROPN cana-3756 97 13 π‘™π‘’π‘Žπ‘Ÿπ‘›π‘Žπ‘π‘™π‘’ π‘™π‘’π‘Žπ‘Ÿπ‘›π‘Žπ‘π‘™π‘’ PROPN cana-3756 97 14 π‘π‘Žπ‘Ÿπ‘Žπ‘šπ‘’π‘‘π‘’π‘Ÿπ‘  π‘π‘Žπ‘Ÿπ‘Žπ‘šπ‘’π‘‘π‘’π‘Ÿπ‘  PROPN cana-3756 97 15 loss loss NOUN cana-3756 97 16 function function NOUN cana-3756 97 17 we we PRON cana-3756 97 18 employ employ VERB cana-3756 97 19 a a DET cana-3756 97 20 weighted weight VERB cana-3756 97 21 categorical categorical ADJ cana-3756 97 22 cross cross ADJ cana-3756 97 23 - - ADJ cana-3756 97 24 entropy entropy ADJ cana-3756 97 25 loss loss NOUN cana-3756 97 26 : : PUNCT cana-3756 97 27 𝐿 𝐿 PROPN cana-3756 97 28 = = NOUN cana-3756 97 29 βˆ’ βˆ’ PROPN cana-3756 97 30 βˆ‘(𝑦𝑖 βˆ‘(𝑦𝑖 PROPN cana-3756 97 31 βˆ— βˆ— PROPN cana-3756 97 32 π‘™π‘œπ‘”(𝑝𝑖 π‘™π‘œπ‘”(𝑝𝑖 PROPN cana-3756 97 33 ) ) PUNCT cana-3756 97 34 βˆ— βˆ— NOUN cana-3756 97 35 𝑀𝑖 𝑀𝑖 NOUN cana-3756 97 36 ) ) PUNCT cana-3756 97 37 𝑦𝑖is 𝑦𝑖i VERB cana-3756 97 38 the the DET cana-3756 97 39 ground ground NOUN cana-3756 97 40 truth truth NOUN cana-3756 97 41 𝑝𝑖 𝑝𝑖 NOUN cana-3756 97 42 is be AUX cana-3756 97 43 the the DET cana-3756 97 44 predicted predict VERB cana-3756 97 45 probability probability NOUN cana-3756 97 46 communications communication NOUN cana-3756 97 47 on on ADP cana-3756 97 48 applied apply VERB cana-3756 97 49 nonlinear nonlinear ADJ cana-3756 97 50 analysis analysis NOUN cana-3756 97 51 issn issn NOUN cana-3756 97 52 : : PUNCT cana-3756 97 53 1074 1074 NUM cana-3756 97 54 - - PUNCT cana-3756 97 55 133x 133x NUM cana-3756 97 56 vol vol NOUN cana-3756 97 57 32 32 NUM cana-3756 97 58 no no NOUN cana-3756 97 59 . . PUNCT cana-3756 98 1 8s 8s PROPN cana-3756 98 2 ( ( PUNCT cana-3756 98 3 2025 2025 NUM cana-3756 98 4 ) ) PUNCT cana-3756 98 5 689 689 NUM cana-3756 98 6 https://internationalpubls.com https://internationalpubls.com X cana-3756 98 7 𝑀𝑖 𝑀𝑖 NOUN cana-3756 98 8 is be AUX cana-3756 98 9 the the DET cana-3756 98 10 class class NOUN cana-3756 98 11 weight weight NOUN cana-3756 98 12 to to PART cana-3756 98 13 handle handle VERB cana-3756 98 14 imbalanced imbalanced ADJ cana-3756 98 15 data datum NOUN cana-3756 98 16 mobilenetv2 mobilenetv2 PROPN cana-3756 98 17 - - PUNCT cana-3756 98 18 lstm lstm NOUN cana-3756 98 19 hybrid hybrid NOUN cana-3756 98 20 the the DET cana-3756 98 21 base base NOUN cana-3756 98 22 design design NOUN cana-3756 98 23 is be AUX cana-3756 98 24 along along ADP cana-3756 98 25 the the DET cana-3756 98 26 lines line NOUN cana-3756 98 27 of of ADP cana-3756 98 28 mobilenetv2 mobilenetv2 PROPN cana-3756 98 29 : : PUNCT cana-3756 98 30 it it PRON cana-3756 98 31 utilizes utilize VERB cana-3756 98 32 depth depth NOUN cana-3756 98 33 - - PUNCT cana-3756 98 34 wise wise ADJ cana-3756 98 35 separable separable ADJ cana-3756 98 36 convolutions convolution NOUN cana-3756 98 37 in in ADP cana-3756 98 38 inverted inverted ADJ cana-3756 98 39 residual residual ADJ cana-3756 98 40 units unit NOUN cana-3756 98 41 . . PUNCT cana-3756 99 1 in in ADP cana-3756 99 2 the the DET cana-3756 99 3 downsampling downsample VERB cana-3756 99 4 layers layer NOUN cana-3756 99 5 , , PUNCT cana-3756 99 6 the the DET cana-3756 99 7 stride stride NOUN cana-3756 99 8 is be AUX cana-3756 99 9 set set VERB cana-3756 99 10 to to ADP cana-3756 99 11 2 2 NUM cana-3756 99 12 , , PUNCT cana-3756 99 13 and and CCONJ cana-3756 99 14 the the DET cana-3756 99 15 expansion expansion NOUN cana-3756 99 16 factor factor NOUN cana-3756 99 17 is be AUX cana-3756 99 18 starting start VERB cana-3756 99 19 at at ADP cana-3756 99 20 6 6 NUM cana-3756 99 21 . . PUNCT cana-3756 100 1 during during ADP cana-3756 100 2 the the DET cana-3756 100 3 execution execution NOUN cana-3756 100 4 of of ADP cana-3756 100 5 an an DET cana-3756 100 6 inverted inverted ADJ cana-3756 100 7 residual residual ADJ cana-3756 100 8 block block NOUN cana-3756 100 9 , , PUNCT cana-3756 100 10 a a DET cana-3756 100 11 lightweight lightweight ADJ cana-3756 100 12 convolution convolution NOUN cana-3756 100 13 is be AUX cana-3756 100 14 used use VERB cana-3756 100 15 as as ADP cana-3756 100 16 an an DET cana-3756 100 17 expansion expansion NOUN cana-3756 100 18 followed follow VERB cana-3756 100 19 by by ADP cana-3756 100 20 depth depth NOUN cana-3756 100 21 - - PUNCT cana-3756 100 22 wise wise ADJ cana-3756 100 23 separable separable ADJ cana-3756 100 24 convolutions convolution NOUN cana-3756 100 25 for for ADP cana-3756 100 26 enhancement enhancement NOUN cana-3756 100 27 , , PUNCT cana-3756 100 28 and and CCONJ cana-3756 100 29 finally finally ADV cana-3756 100 30 , , PUNCT cana-3756 100 31 pointwise pointwise VERB cana-3756 100 32 convolution convolution NOUN cana-3756 100 33 for for ADP cana-3756 100 34 dimensionality dimensionality NOUN cana-3756 100 35 reduction reduction NOUN cana-3756 100 36 . . PUNCT cana-3756 101 1 xβ€² xβ€² X cana-3756 102 1 = = PUNCT cana-3756 102 2 pwconv pwconv INTJ cana-3756 102 3 ( ( PUNCT cana-3756 102 4 dwconv(pwconv(x dwconv(pwconv(x NUM cana-3756 102 5 ) ) PUNCT cana-3756 102 6 ) ) PUNCT cana-3756 102 7 ) ) PUNCT cana-3756 103 1 where where SCONJ cana-3756 103 2 : : PUNCT cana-3756 103 3 pwconv pwconv ADJ cana-3756 103 4 : : PUNCT cana-3756 103 5 point point NOUN cana-3756 103 6 - - PUNCT cana-3756 103 7 wise wise ADJ cana-3756 103 8 convolution convolution NOUN cana-3756 103 9 dwconv dwconv ADJ cana-3756 103 10 : : PUNCT cana-3756 103 11 depth depth NOUN cana-3756 103 12 - - PUNCT cana-3756 103 13 wise wise ADJ cana-3756 103 14 convolution convolution NOUN cana-3756 103 15 x x NOUN cana-3756 103 16 : : PUNCT cana-3756 103 17 input input NOUN cana-3756 103 18 tensor tensor NOUN cana-3756 103 19 temporal temporal ADJ cana-3756 103 20 processing processing NOUN cana-3756 103 21 : : PUNCT cana-3756 103 22 feature feature NOUN cana-3756 103 23 sequence sequence NOUN cana-3756 103 24 generation generation NOUN cana-3756 103 25 lstm lstm NOUN cana-3756 103 26 layer layer NOUN cana-3756 103 27 ( ( PUNCT cana-3756 103 28 256 256 NUM cana-3756 103 29 units unit NOUN cana-3756 103 30 ) ) PUNCT cana-3756 103 31 hidden hide VERB cana-3756 103 32 state state NOUN cana-3756 103 33 equation equation NOUN cana-3756 103 34 : : PUNCT cana-3756 103 35 ht ht PROPN cana-3756 103 36 = = PUNCT cana-3756 103 37 tanh(wh tanh(wh NOUN cana-3756 103 38 Β· Β· PUNCT cana-3756 104 1 [ [ X cana-3756 104 2 htβˆ’1 htβˆ’1 PROPN cana-3756 104 3 , , PUNCT cana-3756 104 4 xt xt ADP cana-3756 104 5 ] ] PUNCT cana-3756 104 6 + + CCONJ cana-3756 104 7 bh bh NOUN cana-3756 104 8 ) ) PUNCT cana-3756 104 9 ct ct PROPN cana-3756 104 10 = = PUNCT cana-3756 104 11 ftctβˆ’1 ftctβˆ’1 PROPN cana-3756 104 12 + + CCONJ cana-3756 104 13 itgt itgt PROPN cana-3756 104 14 ht ht NOUN cana-3756 104 15 : : PUNCT cana-3756 104 16 hiddenstate hiddenstate NOUN cana-3756 104 17 ct ct PROPN cana-3756 104 18 : : PUNCT cana-3756 104 19 cellstate cellstate VERB cana-3756 104 20 ft ft X cana-3756 104 21 : : PUNCT cana-3756 104 22 forgetgate forgetgate VERB cana-3756 104 23 it it PRON cana-3756 104 24 : : PUNCT cana-3756 104 25 inputgate inputgate VERB cana-3756 104 26 g g PROPN cana-3756 104 27 t t PROPN cana-3756 104 28 : : PUNCT cana-3756 104 29 cellupdate cellupdate VERB cana-3756 104 30 βŠ™ βŠ™ PROPN cana-3756 104 31 : : PUNCT cana-3756 104 32 element element VERB cana-3756 104 33 wise wise ADJ cana-3756 104 34 multiplication multiplication NOUN cana-3756 104 35 communications communication NOUN cana-3756 104 36 on on ADP cana-3756 104 37 applied apply VERB cana-3756 104 38 nonlinear nonlinear ADJ cana-3756 104 39 analysis analysis NOUN cana-3756 104 40 issn issn NOUN cana-3756 104 41 : : PUNCT cana-3756 104 42 1074 1074 NUM cana-3756 104 43 - - PUNCT cana-3756 104 44 133x 133x NUM cana-3756 104 45 vol vol NOUN cana-3756 104 46 32 32 NUM cana-3756 104 47 no no NOUN cana-3756 104 48 . . PUNCT cana-3756 105 1 8s 8s PROPN cana-3756 105 2 ( ( PUNCT cana-3756 105 3 2025 2025 NUM cana-3756 105 4 ) ) PUNCT cana-3756 105 5 690 690 NUM cana-3756 106 1 https://internationalpubls.com https://internationalpubls.com X cana-3756 106 2 cnn cnn PROPN cana-3756 106 3 - - PUNCT cana-3756 106 4 lstm lstm ADJ cana-3756 106 5 architecture architecture NOUN cana-3756 106 6 the the DET cana-3756 106 7 output output NOUN cana-3756 106 8 feature feature NOUN cana-3756 106 9 map map NOUN cana-3756 107 1 f f PROPN cana-3756 107 2 at at ADP cana-3756 107 3 each each DET cana-3756 107 4 layer layer NOUN cana-3756 107 5 l l NOUN cana-3756 107 6 is be AUX cana-3756 107 7 computed compute VERB cana-3756 107 8 as as ADP cana-3756 107 9 : : PUNCT cana-3756 107 10 𝐹𝑙 𝐹𝑙 PROPN cana-3756 107 11 = = SYM cana-3756 107 12 π‘€π‘Žπ‘₯π‘ƒπ‘œπ‘œπ‘™ π‘€π‘Žπ‘₯π‘ƒπ‘œπ‘œπ‘™ PROPN cana-3756 107 13 ( ( PUNCT cana-3756 107 14 π‘…π‘’πΏπ‘ˆ π‘…π‘’πΏπ‘ˆ PROPN cana-3756 107 15 ( ( PUNCT cana-3756 107 16 𝐡𝑁(πΆπ‘œπ‘›π‘£(πΉπ‘™βˆ’1 𝐡𝑁(πΆπ‘œπ‘›π‘£(πΉπ‘™βˆ’1 NOUN cana-3756 107 17 ) ) PUNCT cana-3756 107 18 ) ) PUNCT cana-3756 107 19 ) ) PUNCT cana-3756 107 20 ) ) PUNCT cana-3756 107 21 feature feature NOUN cana-3756 107 22 aggregation aggregation NOUN cana-3756 107 23 : : PUNCT cana-3756 107 24 spatial spatial ADJ cana-3756 107 25 attention attention NOUN cana-3756 107 26 mechanism mechanism NOUN cana-3756 107 27 Ξ± Ξ± X cana-3756 107 28 = = SYM cana-3756 107 29 π‘ π‘œπ‘“π‘‘π‘šπ‘Žπ‘₯(π‘Šπ‘Žπ‘‘π‘Žπ‘›β„Ž(π‘Šβ„Žπ» π‘ π‘œπ‘“π‘‘π‘šπ‘Žπ‘₯(π‘Šπ‘Žπ‘‘π‘Žπ‘›β„Ž(π‘Šβ„Žπ» NOUN cana-3756 107 30 ) ) PUNCT cana-3756 107 31 ) ) PUNCT cana-3756 108 1 h h NOUN cana-3756 108 2 : : PUNCT cana-3756 108 3 feature feature NOUN cana-3756 108 4 maps map NOUN cana-3756 108 5 π‘Š_π‘Ž π‘Š_π‘Ž NOUN cana-3756 108 6 , , PUNCT cana-3756 108 7 π‘Š_β„Ž π‘Š_β„Ž NOUN cana-3756 108 8 : : PUNCT cana-3756 108 9 learnable learnable ADJ cana-3756 108 10 parameters parameter NOUN cana-3756 108 11 experimental experimental ADJ cana-3756 108 12 results result NOUN cana-3756 108 13 dataset dataset VERB cana-3756 108 14 and and CCONJ cana-3756 108 15 implementation implementation NOUN cana-3756 108 16 details detail NOUN cana-3756 108 17 utkface utkface NOUN cana-3756 108 18 has have AUX cana-3756 108 19 been be AUX cana-3756 108 20 used use VERB cana-3756 108 21 with with ADP cana-3756 108 22 the the DET cana-3756 108 23 pytorch pytorch NOUN cana-3756 108 24 framework framework NOUN cana-3756 108 25 with with ADP cana-3756 108 26 adam adam PROPN cana-3756 108 27 optimizer optimizer NOUN cana-3756 108 28 and and CCONJ cana-3756 108 29 categorical categorical ADJ cana-3756 108 30 crossentropy crossentropy NOUN cana-3756 108 31 loss loss NOUN cana-3756 108 32 . . PUNCT cana-3756 109 1 table table NOUN cana-3756 109 2 1 1 NUM cana-3756 109 3 : : PUNCT cana-3756 109 4 comparison comparison NOUN cana-3756 109 5 analysis analysis NOUN cana-3756 109 6 of of ADP cana-3756 109 7 models model NOUN cana-3756 109 8 model model NOUN cana-3756 109 9 accuracy accuracy NOUN cana-3756 109 10 precision precision NOUN cana-3756 109 11 recall recall VERB cana-3756 109 12 f1 f1 NOUN cana-3756 109 13 - - PUNCT cana-3756 109 14 score score NOUN cana-3756 109 15 cnn cnn PROPN cana-3756 109 16 0.75 0.75 NUM cana-3756 109 17 0.73 0.73 NUM cana-3756 109 18 0.82 0.82 NUM cana-3756 109 19 0.78 0.78 NUM cana-3756 109 20 cnn cnn NOUN cana-3756 110 1 + + CCONJ cana-3756 110 2 lstm lstm NOUN cana-3756 110 3 0.92 0.92 NUM cana-3756 110 4 0.91 0.91 NUM cana-3756 110 5 0.89 0.89 NUM cana-3756 110 6 0.93 0.93 NUM cana-3756 110 7 lstm lstm NOUN cana-3756 110 8 + + CCONJ cana-3756 110 9 mobilenet mobilenet NOUN cana-3756 110 10 0.92 0.92 NUM cana-3756 110 11 0.87 0.87 NUM cana-3756 110 12 0.91 0.91 NUM cana-3756 110 13 0.85 0.85 NUM cana-3756 110 14 efficientb2 efficientb2 X cana-3756 111 1 + + CCONJ cana-3756 111 2 custom custom NOUN cana-3756 111 3 classifier classifier NOUN cana-3756 111 4 0.96 0.96 NUM cana-3756 111 5 0.93 0.93 NUM cana-3756 111 6 0.94 0.94 NUM cana-3756 111 7 0.89 0.89 NUM cana-3756 111 8 our our PRON cana-3756 111 9 work work NOUN cana-3756 111 10 compared compare VERB cana-3756 111 11 four four NUM cana-3756 111 12 architectures architecture NOUN cana-3756 111 13 for for ADP cana-3756 111 14 human human ADJ cana-3756 111 15 gender gender NOUN cana-3756 111 16 recognition recognition NOUN cana-3756 111 17 in in ADP cana-3756 111 18 terms term NOUN cana-3756 111 19 of of ADP cana-3756 111 20 accuracy accuracy NOUN cana-3756 111 21 , , PUNCT cana-3756 111 22 precision precision NOUN cana-3756 111 23 , , PUNCT cana-3756 111 24 recall recall NOUN cana-3756 111 25 , , PUNCT cana-3756 111 26 and and CCONJ cana-3756 111 27 f1 f1 NOUN cana-3756 111 28 - - PUNCT cana-3756 111 29 score score NOUN cana-3756 111 30 . . PUNCT cana-3756 112 1 the the DET cana-3756 112 2 baseline baseline PROPN cana-3756 112 3 cnn cnn PROPN cana-3756 112 4 model model NOUN cana-3756 112 5 achieved achieve VERB cana-3756 112 6 an an DET cana-3756 112 7 accuracy accuracy NOUN cana-3756 112 8 of of ADP cana-3756 112 9 75 75 NUM cana-3756 112 10 % % NOUN cana-3756 112 11 , , PUNCT cana-3756 112 12 which which PRON cana-3756 112 13 is be AUX cana-3756 112 14 moderate moderate ADJ cana-3756 112 15 but but CCONJ cana-3756 112 16 not not PART cana-3756 112 17 good good ADJ cana-3756 112 18 enough enough ADV cana-3756 112 19 to to PART cana-3756 112 20 handle handle VERB cana-3756 112 21 complex complex ADJ cana-3756 112 22 variations variation NOUN cana-3756 112 23 in in ADP cana-3756 112 24 gender gender NOUN cana-3756 112 25 representation representation NOUN cana-3756 112 26 . . PUNCT cana-3756 113 1 although although SCONJ cana-3756 113 2 it it PRON cana-3756 113 3 had have VERB cana-3756 113 4 a a DET cana-3756 113 5 recall recall NOUN cana-3756 113 6 of of ADP cana-3756 113 7 0.82 0.82 NUM cana-3756 113 8 , , PUNCT cana-3756 113 9 which which PRON cana-3756 113 10 means mean VERB cana-3756 113 11 it it PRON cana-3756 113 12 was be AUX cana-3756 113 13 very very ADV cana-3756 113 14 good good ADJ cana-3756 113 15 at at ADP cana-3756 113 16 detecting detect VERB cana-3756 113 17 positive positive ADJ cana-3756 113 18 cases case NOUN cana-3756 113 19 , , PUNCT cana-3756 113 20 its its PRON cana-3756 113 21 precision precision NOUN cana-3756 113 22 of of ADP cana-3756 113 23 0.73 0.73 NUM cana-3756 113 24 indicates indicate VERB cana-3756 113 25 a a DET cana-3756 113 26 higher high ADJ cana-3756 113 27 rate rate NOUN cana-3756 113 28 of of ADP cana-3756 113 29 false false ADJ cana-3756 113 30 positives positive NOUN cana-3756 113 31 . . PUNCT cana-3756 114 1 this this PRON cana-3756 114 2 makes make VERB cana-3756 114 3 it it PRON cana-3756 114 4 clear clear ADJ cana-3756 114 5 that that SCONJ cana-3756 114 6 the the DET cana-3756 114 7 standalone standalone NOUN cana-3756 114 8 cnn cnn PROPN cana-3756 114 9 can can AUX cana-3756 114 10 not not PART cana-3756 114 11 be be AUX cana-3756 114 12 applied apply VERB cana-3756 114 13 for for ADP cana-3756 114 14 gender gender NOUN cana-3756 114 15 classification classification NOUN cana-3756 114 16 without without ADP cana-3756 114 17 additional additional ADJ cana-3756 114 18 enhancements enhancement NOUN cana-3756 114 19 . . PUNCT cana-3756 115 1 toward toward ADP cana-3756 115 2 this this DET cana-3756 115 3 end end NOUN cana-3756 115 4 , , PUNCT cana-3756 115 5 we we PRON cana-3756 115 6 investigated investigate VERB cana-3756 115 7 hybrids hybrid NOUN cana-3756 115 8 of of ADP cana-3756 115 9 cnn cnn PROPN cana-3756 115 10 and and CCONJ cana-3756 115 11 lstms lstms ADJ cana-3756 115 12 . . PUNCT cana-3756 116 1 the the DET cana-3756 116 2 hybrid hybrid ADJ cana-3756 116 3 cnn cnn PROPN cana-3756 116 4 + + CCONJ cana-3756 116 5 lstm lstm PROPN cana-3756 116 6 model model NOUN cana-3756 116 7 achieved achieve VERB cana-3756 116 8 the the DET cana-3756 116 9 accuracy accuracy NOUN cana-3756 116 10 of of ADP cana-3756 116 11 92 92 NUM cana-3756 116 12 % % NOUN cana-3756 116 13 cnns cnn NOUN cana-3756 116 14 , , PUNCT cana-3756 116 15 for for ADP cana-3756 116 16 spatial spatial ADJ cana-3756 116 17 features feature NOUN cana-3756 116 18 , , PUNCT cana-3756 116 19 and and CCONJ cana-3756 116 20 an an DET cana-3756 116 21 lstm lstm NOUN cana-3756 116 22 for for ADP cana-3756 116 23 a a DET cana-3756 116 24 sequential sequential ADJ cana-3756 116 25 dependency dependency NOUN cana-3756 116 26 communications communication NOUN cana-3756 116 27 on on ADP cana-3756 116 28 applied apply VERB cana-3756 116 29 nonlinear nonlinear ADJ cana-3756 116 30 analysis analysis NOUN cana-3756 116 31 issn issn NOUN cana-3756 116 32 : : PUNCT cana-3756 116 33 1074 1074 NUM cana-3756 116 34 - - PUNCT cana-3756 116 35 133x 133x NUM cana-3756 116 36 vol vol NOUN cana-3756 116 37 32 32 NUM cana-3756 116 38 no no NOUN cana-3756 116 39 . . PUNCT cana-3756 117 1 8s 8s PROPN cana-3756 117 2 ( ( PUNCT cana-3756 117 3 2025 2025 NUM cana-3756 117 4 ) ) PUNCT cana-3756 117 5 691 691 NUM cana-3756 118 1 https://internationalpubls.com https://internationalpubls.com X cana-3756 118 2 context context NOUN cana-3756 118 3 . . PUNCT cana-3756 119 1 similarly similarly ADV cana-3756 119 2 , , PUNCT cana-3756 119 3 the the DET cana-3756 119 4 lstm lstm NOUN cana-3756 119 5 + + CCONJ cana-3756 119 6 mobilenet mobilenet NOUN cana-3756 119 7 had have VERB cana-3756 119 8 an an DET cana-3756 119 9 accuracy accuracy NOUN cana-3756 119 10 level level NOUN cana-3756 119 11 of of ADP cana-3756 119 12 92 92 NUM cana-3756 119 13 % % NOUN cana-3756 119 14 . . PUNCT cana-3756 120 1 however however ADV cana-3756 120 2 , , PUNCT cana-3756 120 3 even even ADV cana-3756 120 4 though though SCONJ cana-3756 120 5 both both CCONJ cana-3756 120 6 the the DET cana-3756 120 7 hybrid hybrid NOUN cana-3756 120 8 models model NOUN cana-3756 120 9 obtained obtain VERB cana-3756 120 10 a a DET cana-3756 120 11 strong strong ADJ cana-3756 120 12 recall recall NOUN cana-3756 120 13 of of ADP cana-3756 120 14 0.89 0.89 NUM cana-3756 120 15 and and CCONJ cana-3756 120 16 0.91 0.91 NUM cana-3756 120 17 , , PUNCT cana-3756 120 18 respectively respectively ADV cana-3756 120 19 , , PUNCT cana-3756 120 20 their their PRON cana-3756 120 21 lower low ADJ cana-3756 120 22 precision precision NOUN cana-3756 120 23 at at ADP cana-3756 120 24 0.91 0.91 NUM cana-3756 120 25 and and CCONJ cana-3756 120 26 0.87 0.87 NUM cana-3756 120 27 points point NOUN cana-3756 120 28 to to ADP cana-3756 120 29 some some DET cana-3756 120 30 cases case NOUN cana-3756 120 31 of of ADP cana-3756 120 32 misclassification misclassification NOUN cana-3756 120 33 . . PUNCT cana-3756 121 1 these these DET cana-3756 121 2 results result NOUN cana-3756 121 3 show show VERB cana-3756 121 4 that that SCONJ cana-3756 121 5 hybrid hybrid NOUN cana-3756 121 6 models model NOUN cana-3756 121 7 are be AUX cana-3756 121 8 considerably considerably ADV cana-3756 121 9 better well ADJ cana-3756 121 10 than than ADP cana-3756 121 11 single single ADJ cana-3756 121 12 cnns cnn NOUN cana-3756 121 13 but but CCONJ cana-3756 121 14 still still ADV cana-3756 121 15 need need VERB cana-3756 121 16 further further ADJ cana-3756 121 17 optimization optimization NOUN cana-3756 121 18 to to PART cana-3756 121 19 boost boost VERB cana-3756 121 20 precision precision NOUN cana-3756 121 21 . . PUNCT cana-3756 122 1 the the DET cana-3756 122 2 best good ADJ cana-3756 122 3 results result NOUN cana-3756 122 4 were be AUX cana-3756 122 5 achieved achieve VERB cana-3756 122 6 in in ADP cana-3756 122 7 the the DET cana-3756 122 8 efficientnetb2 efficientnetb2 NOUN cana-3756 122 9 architecture architecture NOUN cana-3756 122 10 with with ADP cana-3756 122 11 a a DET cana-3756 122 12 classifier classifier NOUN cana-3756 122 13 , , PUNCT cana-3756 122 14 with with ADP cana-3756 122 15 the the DET cana-3756 122 16 accuracy accuracy NOUN cana-3756 122 17 being be AUX cana-3756 122 18 up up ADV cana-3756 122 19 to to PART cana-3756 122 20 96 96 NUM cana-3756 122 21 % % NOUN cana-3756 122 22 , , PUNCT cana-3756 122 23 precision precision NOUN cana-3756 122 24 equals equal VERB cana-3756 122 25 0.93 0.93 NUM cana-3756 122 26 , , PUNCT cana-3756 122 27 and and CCONJ cana-3756 122 28 recall recall NOUN cana-3756 122 29 equals equal VERB cana-3756 122 30 0.94 0.94 NUM cana-3756 122 31 . . PUNCT cana-3756 123 1 this this PRON cana-3756 123 2 has have AUX cana-3756 123 3 been be AUX cana-3756 123 4 possible possible ADJ cana-3756 123 5 only only ADV cana-3756 123 6 due due ADJ cana-3756 123 7 to to ADP cana-3756 123 8 optimizing optimize VERB cana-3756 123 9 feature feature NOUN cana-3756 123 10 extraction extraction NOUN cana-3756 123 11 during during ADP cana-3756 123 12 the the DET cana-3756 123 13 training training NOUN cana-3756 123 14 on on ADP cana-3756 123 15 efficientnetb2 efficientnetb2 X cana-3756 123 16 , , PUNCT cana-3756 123 17 further far ADV cana-3756 123 18 improving improve VERB cana-3756 123 19 generalizability generalizability NOUN cana-3756 123 20 across across ADP cana-3756 123 21 very very ADV cana-3756 123 22 different different ADJ cana-3756 123 23 datasets dataset NOUN cana-3756 123 24 . . PUNCT cana-3756 124 1 this this DET cana-3756 124 2 model model NOUN cana-3756 124 3 balanced balanced ADJ cana-3756 124 4 accuracy accuracy NOUN cana-3756 124 5 , , PUNCT cana-3756 124 6 efficiency efficiency NOUN cana-3756 124 7 , , PUNCT cana-3756 124 8 and and CCONJ cana-3756 124 9 potential potential ADJ cana-3756 124 10 real real ADJ cana-3756 124 11 - - PUNCT cana-3756 124 12 world world NOUN cana-3756 124 13 usages usage NOUN cana-3756 124 14 better well ADV cana-3756 124 15 compared compare VERB cana-3756 124 16 to to ADP cana-3756 124 17 other other ADJ cana-3756 124 18 methods method NOUN cana-3756 124 19 and and CCONJ cana-3756 124 20 can can AUX cana-3756 124 21 , , PUNCT cana-3756 124 22 therefore therefore ADV cana-3756 124 23 , , PUNCT cana-3756 124 24 find find VERB cana-3756 124 25 its its PRON cana-3756 124 26 application application NOUN cana-3756 124 27 mainly mainly ADV cana-3756 124 28 in in ADP cana-3756 124 29 biometric biometric ADJ cana-3756 124 30 , , PUNCT cana-3756 124 31 security security NOUN cana-3756 124 32 issues issue NOUN cana-3756 124 33 , , PUNCT cana-3756 124 34 and and CCONJ cana-3756 124 35 more more ADJ cana-3756 124 36 ai ai AUX cana-3756 124 37 - - PUNCT cana-3756 124 38 driven drive VERB cana-3756 124 39 forms form NOUN cana-3756 124 40 of of ADP cana-3756 124 41 personalization personalization NOUN cana-3756 124 42 . . PUNCT cana-3756 125 1 looking look VERB cana-3756 125 2 forward forward ADV cana-3756 125 3 , , PUNCT cana-3756 125 4 we we PRON cana-3756 125 5 will will AUX cana-3756 125 6 incorporate incorporate VERB cana-3756 125 7 attention attention NOUN cana-3756 125 8 mechanisms mechanism NOUN cana-3756 125 9 and and CCONJ cana-3756 125 10 multi multi ADJ cana-3756 125 11 - - NOUN cana-3756 125 12 task task ADJ cana-3756 125 13 learning learning NOUN cana-3756 125 14 to to PART cana-3756 125 15 further further VERB cana-3756 125 16 fine fine ADJ cana-3756 125 17 - - PUNCT cana-3756 125 18 tune tune NOUN cana-3756 125 19 the the DET cana-3756 125 20 performance performance NOUN cana-3756 125 21 of of ADP cana-3756 125 22 the the DET cana-3756 125 23 model model NOUN cana-3756 125 24 , , PUNCT cana-3756 125 25 thereby thereby ADV cana-3756 125 26 ensuring ensure VERB cana-3756 125 27 even even ADV cana-3756 125 28 greater great ADJ cana-3756 125 29 robustness robustness NOUN cana-3756 125 30 and and CCONJ cana-3756 125 31 reliability reliability NOUN cana-3756 125 32 in in ADP cana-3756 125 33 real real ADJ cana-3756 125 34 - - PUNCT cana-3756 125 35 world world NOUN cana-3756 125 36 scenarios scenario NOUN cana-3756 125 37 . . PUNCT cana-3756 126 1 figure figure VERB cana-3756 126 2 1 1 NUM cana-3756 126 3 : : PUNCT cana-3756 126 4 comparison comparison NOUN cana-3756 126 5 of of ADP cana-3756 126 6 models model NOUN cana-3756 126 7 : : PUNCT cana-3756 126 8 accuracy accuracy NOUN cana-3756 126 9 , , PUNCT cana-3756 126 10 precision precision NOUN cana-3756 126 11 , , PUNCT cana-3756 126 12 recall recall NOUN cana-3756 126 13 and and CCONJ cana-3756 126 14 f1 f1 PROPN cana-3756 126 15 score score NOUN cana-3756 126 16 figure figure NOUN cana-3756 126 17 2 2 NUM cana-3756 126 18 : : PUNCT cana-3756 126 19 analysis analysis NOUN cana-3756 126 20 of of ADP cana-3756 126 21 different different ADJ cana-3756 126 22 models model NOUN cana-3756 126 23 accuracy accuracy NOUN cana-3756 126 24 sample sample NOUN cana-3756 126 25 input input NOUN cana-3756 126 26 and and CCONJ cana-3756 126 27 output output NOUN cana-3756 126 28 predicted predict VERB cana-3756 126 29 output output NOUN cana-3756 126 30 : : PUNCT cana-3756 126 31 male male ADJ cana-3756 126 32 predicted predict VERB cana-3756 126 33 output output NOUN cana-3756 126 34 : : PUNCT cana-3756 126 35 male male ADJ cana-3756 126 36 predicted predict VERB cana-3756 126 37 output output NOUN cana-3756 126 38 : : PUNCT cana-3756 126 39 male male ADJ cana-3756 126 40 confidence confidence NOUN cana-3756 126 41 : : PUNCT cana-3756 126 42 95 95 NUM cana-3756 126 43 confidence confidence NOUN cana-3756 126 44 : : PUNCT cana-3756 126 45 89 89 NUM cana-3756 126 46 confidence confidence NOUN cana-3756 126 47 : : PUNCT cana-3756 126 48 92 92 NUM cana-3756 126 49 predicted predict VERB cana-3756 126 50 output output NOUN cana-3756 126 51 : : PUNCT cana-3756 126 52 female female ADJ cana-3756 126 53 predicted predict VERB cana-3756 126 54 output output NOUN cana-3756 126 55 : : PUNCT cana-3756 126 56 female female ADJ cana-3756 126 57 predicted predict VERB cana-3756 126 58 output output NOUN cana-3756 126 59 : : PUNCT cana-3756 126 60 female female ADJ cana-3756 126 61 confidence confidence NOUN cana-3756 126 62 : : PUNCT cana-3756 126 63 90 90 NUM cana-3756 126 64 confidence confidence NOUN cana-3756 126 65 : : PUNCT cana-3756 126 66 79 79 NUM cana-3756 126 67 confidence confidence NOUN cana-3756 126 68 : : PUNCT cana-3756 126 69 85 85 NUM cana-3756 126 70 communications communication NOUN cana-3756 126 71 on on ADP cana-3756 126 72 applied apply VERB cana-3756 126 73 nonlinear nonlinear ADJ cana-3756 126 74 analysis analysis NOUN cana-3756 126 75 issn issn NOUN cana-3756 126 76 : : PUNCT cana-3756 126 77 1074 1074 NUM cana-3756 126 78 - - PUNCT cana-3756 126 79 133x 133x NUM cana-3756 126 80 vol vol NOUN cana-3756 126 81 32 32 NUM cana-3756 126 82 no no NOUN cana-3756 126 83 . . PUNCT cana-3756 127 1 8s 8s PROPN cana-3756 127 2 ( ( PUNCT cana-3756 127 3 2025 2025 NUM cana-3756 127 4 ) ) PUNCT cana-3756 127 5 692 692 NUM cana-3756 127 6 https://internationalpubls.com https://internationalpubls.com X cana-3756 127 7 conclusion conclusion NOUN cana-3756 127 8 we we PRON cana-3756 127 9 have have AUX cana-3756 127 10 presented present VERB cana-3756 127 11 three three NUM cana-3756 127 12 novel novel ADJ cana-3756 127 13 architectures architecture NOUN cana-3756 127 14 for for ADP cana-3756 127 15 human human ADJ cana-3756 127 16 gender gender NOUN cana-3756 127 17 recognition recognition NOUN cana-3756 127 18 . . PUNCT cana-3756 128 1 the the DET cana-3756 128 2 primary primary ADJ cana-3756 128 3 model model NOUN cana-3756 128 4 that that PRON cana-3756 128 5 we we PRON cana-3756 128 6 introduced introduce VERB cana-3756 128 7 here here ADV cana-3756 128 8 is be AUX cana-3756 128 9 based base VERB cana-3756 128 10 on on ADP cana-3756 128 11 efficientnetb2 efficientnetb2 NOUN cana-3756 128 12 and and CCONJ cana-3756 128 13 reached reach VERB cana-3756 128 14 an an DET cana-3756 128 15 impressive impressive ADJ cana-3756 128 16 accuracy accuracy NOUN cana-3756 128 17 of of ADP cana-3756 128 18 96.73 96.73 NUM cana-3756 128 19 % % NOUN cana-3756 128 20 . . PUNCT cana-3756 129 1 this this DET cana-3756 129 2 architecture architecture NOUN cana-3756 129 3 performs perform VERB cana-3756 129 4 better well ADJ cana-3756 129 5 than than ADP cana-3756 129 6 all all DET cana-3756 129 7 the the DET cana-3756 129 8 solutions solution NOUN cana-3756 129 9 so so ADV cana-3756 129 10 far far ADV cana-3756 129 11 presented present VERB cana-3756 129 12 and and CCONJ cana-3756 129 13 is be AUX cana-3756 129 14 strong strong ADJ cana-3756 129 15 for for ADP cana-3756 129 16 real real ADJ cana-3756 129 17 - - PUNCT cana-3756 129 18 world world NOUN cana-3756 129 19 applications application NOUN cana-3756 129 20 . . PUNCT cana-3756 130 1 further far ADV cana-3756 130 2 , , PUNCT cana-3756 130 3 we we PRON cana-3756 130 4 experiment experiment VERB cana-3756 130 5 with with ADP cana-3756 130 6 hybrid hybrid ADJ cana-3756 130 7 architectures architecture NOUN cana-3756 130 8 combining combine VERB cana-3756 130 9 convolutional convolutional ADJ cana-3756 130 10 and and CCONJ cana-3756 130 11 recurrent recurrent ADJ cana-3756 130 12 neural neural ADJ cana-3756 130 13 network network NOUN cana-3756 130 14 components component NOUN cana-3756 130 15 . . PUNCT cana-3756 131 1 the the DET cana-3756 131 2 hybrid hybrid ADJ cana-3756 131 3 architectures architecture NOUN cana-3756 131 4 failed fail VERB cana-3756 131 5 to to PART cana-3756 131 6 match match VERB cana-3756 131 7 the the DET cana-3756 131 8 accuracy accuracy NOUN cana-3756 131 9 achieved achieve VERB cana-3756 131 10 by by ADP cana-3756 131 11 our our PRON cana-3756 131 12 proposed propose VERB cana-3756 131 13 efficientnetb2 efficientnetb2 X cana-3756 131 14 - - PUNCT cana-3756 131 15 based base VERB cana-3756 131 16 solution solution NOUN cana-3756 131 17 , , PUNCT cana-3756 131 18 but but CCONJ cana-3756 131 19 are be AUX cana-3756 131 20 informative informative ADJ cana-3756 131 21 in in ADP cana-3756 131 22 discussing discuss VERB cana-3756 131 23 potential potential ADJ cana-3756 131 24 benefits benefit NOUN cana-3756 131 25 that that PRON cana-3756 131 26 might might AUX cana-3756 131 27 be be AUX cana-3756 131 28 garnered garner VERB cana-3756 131 29 by by ADP cana-3756 131 30 combining combine VERB cana-3756 131 31 disparate disparate ADJ cana-3756 131 32 architectural architectural ADJ cana-3756 131 33 paradigms paradigm NOUN cana-3756 131 34 . . PUNCT cana-3756 132 1 this this PRON cana-3756 132 2 is be AUX cana-3756 132 3 particularly particularly ADV cana-3756 132 4 exemplified exemplify VERB cana-3756 132 5 in in ADP cana-3756 132 6 the the DET cana-3756 132 7 case case NOUN cana-3756 132 8 of of ADP cana-3756 132 9 integrating integrate VERB cana-3756 132 10 convolutional convolutional ADJ cana-3756 132 11 networks network NOUN cana-3756 132 12 to to PART cana-3756 132 13 extract extract VERB cana-3756 132 14 spatial spatial ADJ cana-3756 132 15 features feature NOUN cana-3756 132 16 and and CCONJ cana-3756 132 17 recurrent recurrent ADJ cana-3756 132 18 layers layer NOUN cana-3756 132 19 to to PART cana-3756 132 20 learn learn VERB cana-3756 132 21 sequential sequential ADJ cana-3756 132 22 dependencies dependency NOUN cana-3756 132 23 , , PUNCT cana-3756 132 24 improving improve VERB cana-3756 132 25 gender gender NOUN cana-3756 132 26 recognition recognition NOUN cana-3756 132 27 systems system NOUN cana-3756 132 28 . . PUNCT cana-3756 133 1 looking look VERB cana-3756 133 2 ahead ahead ADV cana-3756 133 3 , , PUNCT cana-3756 133 4 we we PRON cana-3756 133 5 hope hope VERB cana-3756 133 6 to to PART cana-3756 133 7 take take VERB cana-3756 133 8 performance performance NOUN cana-3756 133 9 of of ADP cana-3756 133 10 models model NOUN cana-3756 133 11 even even ADV cana-3756 133 12 further far ADV cana-3756 133 13 through through ADP cana-3756 133 14 incorporating incorporate VERB cana-3756 133 15 attention attention NOUN cana-3756 133 16 mechanisms mechanism NOUN cana-3756 133 17 in in ADP cana-3756 133 18 improving improve VERB cana-3756 133 19 the the DET cana-3756 133 20 feature feature NOUN cana-3756 133 21 selection selection NOUN cana-3756 133 22 along along ADP cana-3756 133 23 with with ADP cana-3756 133 24 multi multi ADJ cana-3756 133 25 - - ADJ cana-3756 133 26 task task ADJ cana-3756 133 27 learning learning NOUN cana-3756 133 28 strategies strategy NOUN cana-3756 133 29 and and CCONJ cana-3756 133 30 utilize utilize VERB cana-3756 133 31 auxiliary auxiliary ADJ cana-3756 133 32 tasks task NOUN cana-3756 133 33 to to PART cana-3756 133 34 achieve achieve VERB cana-3756 133 35 improved improved ADJ cana-3756 133 36 generalization generalization NOUN cana-3756 133 37 . . PUNCT cana-3756 134 1 this this PRON cana-3756 134 2 might might AUX cana-3756 134 3 fine fine ADV cana-3756 134 4 - - PUNCT cana-3756 134 5 tune tune NOUN cana-3756 134 6 the the DET cana-3756 134 7 accuracy accuracy NOUN cana-3756 134 8 and and CCONJ cana-3756 134 9 robustness robustness NOUN cana-3756 134 10 in in ADP cana-3756 134 11 a a DET cana-3756 134 12 much much ADV cana-3756 134 13 challenging challenging ADJ cana-3756 134 14 environment environment NOUN cana-3756 134 15 that that PRON cana-3756 134 16 has have VERB cana-3756 134 17 variations variation NOUN cana-3756 134 18 of of ADP cana-3756 134 19 lighting lighting NOUN cana-3756 134 20 , , PUNCT cana-3756 134 21 poses pose NOUN cana-3756 134 22 , , PUNCT cana-3756 134 23 and and CCONJ cana-3756 134 24 occlusions occlusion NOUN cana-3756 134 25 of of ADP cana-3756 134 26 the the DET cana-3756 134 27 realworld realworld PROPN cana-3756 134 28 setting setting NOUN cana-3756 134 29 . . PUNCT cana-3756 135 1 references reference NOUN cana-3756 135 2 [ [ X cana-3756 135 3 1 1 NUM cana-3756 135 4 ] ] PUNCT cana-3756 135 5 g. g. PROPN cana-3756 135 6 levi levi PROPN cana-3756 135 7 and and CCONJ cana-3756 135 8 t. t. PROPN cana-3756 135 9 hassner hassner NOUN cana-3756 135 10 , , PUNCT cana-3756 135 11 " " PUNCT cana-3756 135 12 age age NOUN cana-3756 135 13 and and CCONJ cana-3756 135 14 gender gender NOUN cana-3756 135 15 classification classification NOUN cana-3756 135 16 using use VERB cana-3756 135 17 convolutional convolutional ADJ cana-3756 135 18 neural neural ADJ cana-3756 135 19 networks network NOUN cana-3756 135 20 , , PUNCT cana-3756 135 21 " " PUNCT cana-3756 135 22 in in ADP cana-3756 135 23 proc proc NOUN cana-3756 135 24 . . PUNCT cana-3756 136 1 ieee ieee NOUN cana-3756 136 2 conf conf NOUN cana-3756 136 3 . . PUNCT cana-3756 137 1 comput comput NOUN cana-3756 137 2 . . PUNCT cana-3756 138 1 vis vis X cana-3756 138 2 . . X cana-3756 138 3 pattern pattern NOUN cana-3756 138 4 recognit recognit VERB cana-3756 138 5 . . PUNCT cana-3756 139 1 workshops workshop NOUN cana-3756 139 2 , , PUNCT cana-3756 139 3 2015 2015 NUM cana-3756 139 4 , , PUNCT cana-3756 139 5 pp pp ADJ cana-3756 139 6 . . PUNCT cana-3756 140 1 34 34 NUM cana-3756 140 2 - - SYM cana-3756 140 3 42 42 NUM cana-3756 140 4 . . PUNCT cana-3756 141 1 [ [ X cana-3756 141 2 2 2 X cana-3756 141 3 ] ] PUNCT cana-3756 141 4 j. j. PROPN cana-3756 141 5 wang wang PROPN cana-3756 141 6 , , PUNCT cana-3756 141 7 y. y. PROPN cana-3756 141 8 li li PROPN cana-3756 141 9 , , PUNCT cana-3756 141 10 and and CCONJ cana-3756 141 11 d. d. PROPN cana-3756 141 12 zhang zhang PROPN cana-3756 141 13 , , PUNCT cana-3756 141 14 " " PUNCT cana-3756 141 15 multi multi ADJ cana-3756 141 16 - - ADJ cana-3756 141 17 task task ADJ cana-3756 141 18 deep deep ADJ cana-3756 141 19 learning learning NOUN cana-3756 141 20 for for ADP cana-3756 141 21 gender gender NOUN cana-3756 141 22 and and CCONJ cana-3756 141 23 age age NOUN cana-3756 141 24 classification classification NOUN cana-3756 141 25 , , PUNCT cana-3756 141 26 " " PUNCT cana-3756 141 27 pattern pattern NOUN cana-3756 141 28 recognit recognit VERB cana-3756 141 29 . . PUNCT cana-3756 142 1 lett lett PROPN cana-3756 142 2 . . PROPN cana-3756 142 3 , , PUNCT cana-3756 142 4 vol vol NOUN cana-3756 142 5 . . PROPN cana-3756 142 6 83 83 NUM cana-3756 142 7 , , PUNCT cana-3756 142 8 pp pp ADJ cana-3756 142 9 . . PUNCT cana-3756 143 1 219 219 NUM cana-3756 143 2 - - SYM cana-3756 143 3 226 226 NUM cana-3756 143 4 , , PUNCT cana-3756 143 5 2016 2016 NUM cana-3756 143 6 . . PUNCT cana-3756 144 1 [ [ X cana-3756 144 2 3 3 X cana-3756 144 3 ] ] PUNCT cana-3756 144 4 s. s. PROPN cana-3756 144 5 liu liu PROPN cana-3756 144 6 and and CCONJ cana-3756 144 7 y. y. PROPN cana-3756 144 8 zhang zhang PROPN cana-3756 144 9 , , PUNCT cana-3756 144 10 " " PUNCT cana-3756 144 11 lightweight lightweight ADJ cana-3756 144 12 convolutional convolutional ADJ cana-3756 144 13 neural neural ADJ cana-3756 144 14 networks network NOUN cana-3756 144 15 for for ADP cana-3756 144 16 mobile mobile ADJ cana-3756 144 17 gender gender NOUN cana-3756 144 18 recognition recognition NOUN cana-3756 144 19 , , PUNCT cana-3756 144 20 " " PUNCT cana-3756 144 21 in in ADP cana-3756 144 22 int int PROPN cana-3756 144 23 . . PUNCT cana-3756 144 24 conf conf PROPN cana-3756 144 25 . . PUNCT cana-3756 145 1 comput comput NOUN cana-3756 145 2 . . PUNCT cana-3756 146 1 vis vis X cana-3756 146 2 . . PUNCT cana-3756 147 1 syst syst PROPN cana-3756 147 2 . . PROPN cana-3756 147 3 , , PUNCT cana-3756 147 4 2017 2017 NUM cana-3756 147 5 , , PUNCT cana-3756 147 6 pp pp ADJ cana-3756 147 7 . . PUNCT cana-3756 148 1 108 108 NUM cana-3756 148 2 - - SYM cana-3756 148 3 117 117 NUM cana-3756 148 4 . . PUNCT cana-3756 149 1 [ [ X cana-3756 149 2 4 4 X cana-3756 149 3 ] ] PUNCT cana-3756 149 4 x. x. PROPN cana-3756 149 5 chen chen PROPN cana-3756 149 6 , , PUNCT cana-3756 149 7 q. q. PROPN cana-3756 149 8 li li PROPN cana-3756 149 9 , , PUNCT cana-3756 149 10 and and CCONJ cana-3756 149 11 r. r. PROPN cana-3756 149 12 wang wang PROPN cana-3756 149 13 , , PUNCT cana-3756 149 14 " " PUNCT cana-3756 149 15 deep deep ADJ cana-3756 149 16 residual residual ADJ cana-3756 149 17 networks network NOUN cana-3756 149 18 for for ADP cana-3756 149 19 gender gender NOUN cana-3756 149 20 recognition recognition NOUN cana-3756 149 21 from from ADP cana-3756 149 22 facial facial ADJ cana-3756 149 23 images image NOUN cana-3756 149 24 , , PUNCT cana-3756 149 25 " " PUNCT cana-3756 149 26 ieee ieee NOUN cana-3756 149 27 trans tran NOUN cana-3756 149 28 . . PUNCT cana-3756 149 29 pattern pattern PROPN cana-3756 149 30 anal anal PROPN cana-3756 149 31 . . PUNCT cana-3756 150 1 mach mach PROPN cana-3756 150 2 . . PUNCT cana-3756 151 1 intell intell PROPN cana-3756 151 2 . . PUNCT cana-3756 152 1 , , PUNCT cana-3756 152 2 vol vol NOUN cana-3756 152 3 . . PROPN cana-3756 153 1 40 40 NUM cana-3756 153 2 , , PUNCT cana-3756 153 3 no no INTJ cana-3756 153 4 . . NOUN cana-3756 153 5 8 8 NUM cana-3756 153 6 , , PUNCT cana-3756 153 7 pp pp ADJ cana-3756 153 8 . . PUNCT cana-3756 154 1 1812 1812 NUM cana-3756 154 2 - - SYM cana-3756 154 3 1823 1823 NUM cana-3756 154 4 , , PUNCT cana-3756 154 5 2018 2018 NUM cana-3756 154 6 . . PUNCT cana-3756 155 1 [ [ X cana-3756 155 2 5 5 X cana-3756 155 3 ] ] PUNCT cana-3756 155 4 z. z. PROPN cana-3756 155 5 yang yang PROPN cana-3756 155 6 , , PUNCT cana-3756 155 7 h. h. PROPN cana-3756 155 8 yu yu PROPN cana-3756 155 9 , , PUNCT cana-3756 155 10 and and CCONJ cana-3756 155 11 m. m. PROPN cana-3756 155 12 yang yang PROPN cana-3756 155 13 , , PUNCT cana-3756 155 14 " " PUNCT cana-3756 155 15 shufflenet shufflenet NOUN cana-3756 155 16 : : PUNCT cana-3756 155 17 an an DET cana-3756 155 18 extremely extremely ADV cana-3756 155 19 efficient efficient ADJ cana-3756 155 20 convolutional convolutional ADJ cana-3756 155 21 neural neural ADJ cana-3756 155 22 network network NOUN cana-3756 155 23 for for ADP cana-3756 155 24 gender gender NOUN cana-3756 155 25 classification classification NOUN cana-3756 155 26 , , PUNCT cana-3756 155 27 " " PUNCT cana-3756 155 28 ieee ieee NOUN cana-3756 155 29 access access NOUN cana-3756 155 30 , , PUNCT cana-3756 155 31 vol vol NOUN cana-3756 155 32 . . PROPN cana-3756 155 33 6 6 NUM cana-3756 155 34 , , PUNCT cana-3756 155 35 pp pp ADJ cana-3756 155 36 . . PUNCT cana-3756 156 1 73619 73619 NUM cana-3756 156 2 - - SYM cana-3756 156 3 73628 73628 NUM cana-3756 156 4 , , PUNCT cana-3756 156 5 2018 2018 NUM cana-3756 156 6 . . PUNCT cana-3756 157 1 [ [ X cana-3756 157 2 6 6 NUM cana-3756 157 3 ] ] X cana-3756 157 4 g. g. PROPN cana-3756 157 5 azzopardi azzopardi PROPN cana-3756 157 6 , , PUNCT cana-3756 157 7 a. a. PROPN cana-3756 157 8 greco greco PROPN cana-3756 157 9 , , PUNCT cana-3756 157 10 and and CCONJ cana-3756 157 11 m. m. NOUN cana-3756 157 12 vento vento PROPN cana-3756 157 13 , , PUNCT cana-3756 157 14 " " PUNCT cana-3756 157 15 gender gender NOUN cana-3756 157 16 recognition recognition NOUN cana-3756 157 17 from from ADP cana-3756 157 18 face face NOUN cana-3756 157 19 images image NOUN cana-3756 157 20 using use VERB cana-3756 157 21 vgg vgg NOUN cana-3756 157 22 - - PUNCT cana-3756 157 23 based base VERB cana-3756 157 24 architecture architecture NOUN cana-3756 157 25 , , PUNCT cana-3756 157 26 " " PUNCT cana-3756 157 27 pattern pattern NOUN cana-3756 157 28 recognit recognit VERB cana-3756 157 29 . . PUNCT cana-3756 158 1 lett lett PROPN cana-3756 158 2 . . PROPN cana-3756 158 3 , , PUNCT cana-3756 158 4 vol vol NOUN cana-3756 158 5 . . PROPN cana-3756 158 6 128 128 NUM cana-3756 158 7 , , PUNCT cana-3756 158 8 pp pp ADJ cana-3756 158 9 . . PUNCT cana-3756 159 1 386 386 NUM cana-3756 159 2 - - SYM cana-3756 159 3 392 392 NUM cana-3756 159 4 , , PUNCT cana-3756 159 5 2019 2019 NUM cana-3756 159 6 . . PUNCT cana-3756 160 1 [ [ X cana-3756 160 2 7 7 X cana-3756 160 3 ] ] X cana-3756 160 4 w. w. PROPN cana-3756 160 5 zhang zhang PROPN cana-3756 160 6 and and CCONJ cana-3756 160 7 h. h. PROPN cana-3756 160 8 liu liu PROPN cana-3756 160 9 , , PUNCT cana-3756 160 10 " " PUNCT cana-3756 160 11 attention attention NOUN cana-3756 160 12 - - PUNCT cana-3756 160 13 guided guide VERB cana-3756 160 14 gender gender NOUN cana-3756 160 15 recognition recognition NOUN cana-3756 160 16 from from ADP cana-3756 160 17 facial facial ADJ cana-3756 160 18 images image NOUN cana-3756 160 19 , , PUNCT cana-3756 160 20 " " PUNCT cana-3756 160 21 ieee ieee NOUN cana-3756 160 22 trans trans PROPN cana-3756 160 23 . . PROPN cana-3756 160 24 inf inf PROPN cana-3756 160 25 . . PUNCT cana-3756 160 26 forensics forensic NOUN cana-3756 160 27 security security NOUN cana-3756 160 28 , , PUNCT cana-3756 160 29 vol vol NOUN cana-3756 160 30 . . PROPN cana-3756 160 31 15 15 NUM cana-3756 160 32 , , PUNCT cana-3756 160 33 pp pp ADJ cana-3756 160 34 . . PUNCT cana-3756 161 1 3428 3428 NUM cana-3756 161 2 - - SYM cana-3756 161 3 3439 3439 NUM cana-3756 161 4 , , PUNCT cana-3756 161 5 2020 2020 NUM cana-3756 161 6 . . PUNCT cana-3756 162 1 [ [ X cana-3756 162 2 8 8 NUM cana-3756 162 3 ] ] X cana-3756 162 4 r. r. PROPN cana-3756 162 5 kumar kumar PROPN cana-3756 162 6 and and CCONJ cana-3756 162 7 v. v. ADP cana-3756 162 8 m. m. NOUN cana-3756 162 9 patel patel PROPN cana-3756 162 10 , , PUNCT cana-3756 162 11 " " PUNCT cana-3756 162 12 channel channel NOUN cana-3756 162 13 attention attention NOUN cana-3756 162 14 networks network NOUN cana-3756 162 15 for for ADP cana-3756 162 16 robust robust ADJ cana-3756 162 17 gender gender NOUN cana-3756 162 18 recognition recognition NOUN cana-3756 162 19 , , PUNCT cana-3756 162 20 " " PUNCT cana-3756 162 21 in in ADP cana-3756 162 22 proc proc NOUN cana-3756 162 23 . . PUNCT cana-3756 163 1 ieee ieee NOUN cana-3756 163 2 conf conf NOUN cana-3756 163 3 . . PUNCT cana-3756 164 1 comput comput NOUN cana-3756 164 2 . . PUNCT cana-3756 165 1 vis vis X cana-3756 165 2 . . X cana-3756 165 3 pattern pattern NOUN cana-3756 165 4 recognit recognit VERB cana-3756 165 5 . . PROPN cana-3756 165 6 , , PUNCT cana-3756 165 7 2020 2020 NUM cana-3756 165 8 , , PUNCT cana-3756 165 9 pp pp ADV cana-3756 165 10 . . PUNCT cana-3756 165 11 4247 4247 NUM cana-3756 165 12 - - SYM cana-3756 165 13 4256 4256 NUM cana-3756 165 14 . . PUNCT cana-3756 166 1 [ [ X cana-3756 166 2 9 9 NUM cana-3756 166 3 ] ] PUNCT cana-3756 166 4 a. a. NOUN cana-3756 166 5 singh singh PROPN cana-3756 166 6 , , PUNCT cana-3756 166 7 d. d. PROPN cana-3756 166 8 patil patil PROPN cana-3756 166 9 , , PUNCT cana-3756 166 10 and and CCONJ cana-3756 166 11 s. s. PROPN cana-3756 166 12 n. n. PROPN cana-3756 166 13 omkar omkar PROPN cana-3756 166 14 , , PUNCT cana-3756 166 15 " " PUNCT cana-3756 166 16 transfer transfer NOUN cana-3756 166 17 learning learning NOUN cana-3756 166 18 with with ADP cana-3756 166 19 densenet121 densenet121 PROPN cana-3756 166 20 for for ADP cana-3756 166 21 gender gender NOUN cana-3756 166 22 classification classification NOUN cana-3756 166 23 , , PUNCT cana-3756 166 24 " " PUNCT cana-3756 166 25 neural neural ADJ cana-3756 166 26 comput comput NOUN cana-3756 166 27 . . PUNCT cana-3756 167 1 appl appl PROPN cana-3756 167 2 . . PROPN cana-3756 167 3 , , PUNCT cana-3756 167 4 vol vol NOUN cana-3756 167 5 . . PROPN cana-3756 168 1 33 33 NUM cana-3756 168 2 , , PUNCT cana-3756 168 3 no no INTJ cana-3756 168 4 . . NOUN cana-3756 168 5 9 9 NUM cana-3756 168 6 , , PUNCT cana-3756 168 7 pp pp ADJ cana-3756 168 8 . . PUNCT cana-3756 169 1 4445 4445 NUM cana-3756 169 2 - - SYM cana-3756 169 3 4456 4456 NUM cana-3756 169 4 , , PUNCT cana-3756 169 5 2021 2021 NUM cana-3756 169 6 . . PUNCT cana-3756 170 1 [ [ X cana-3756 170 2 10 10 NUM cana-3756 170 3 ] ] X cana-3756 170 4 j. j. PROPN cana-3756 170 5 park park PROPN cana-3756 170 6 , , PUNCT cana-3756 170 7 s. s. PROPN cana-3756 170 8 kim kim PROPN cana-3756 170 9 , , PUNCT cana-3756 170 10 and and CCONJ cana-3756 170 11 m. m. PROPN cana-3756 170 12 lee lee PROPN cana-3756 170 13 , , PUNCT cana-3756 170 14 " " PUNCT cana-3756 170 15 transformer transformer NOUN cana-3756 170 16 - - PUNCT cana-3756 170 17 cnn cnn NOUN cana-3756 170 18 hybrid hybrid ADJ cana-3756 170 19 architecture architecture NOUN cana-3756 170 20 for for ADP cana-3756 170 21 facial facial ADJ cana-3756 170 22 gender gender NOUN cana-3756 170 23 recognition recognition NOUN cana-3756 170 24 , , PUNCT cana-3756 170 25 " " PUNCT cana-3756 170 26 ieee ieee NOUN cana-3756 170 27 access access NOUN cana-3756 170 28 , , PUNCT cana-3756 170 29 vol vol NOUN cana-3756 170 30 . . NOUN cana-3756 170 31 9 9 NUM cana-3756 170 32 , , PUNCT cana-3756 170 33 pp pp ADJ cana-3756 170 34 . . PUNCT cana-3756 171 1 123456 123456 NUM cana-3756 171 2 - - SYM cana-3756 171 3 123467 123467 NUM cana-3756 171 4 , , PUNCT cana-3756 171 5 2021 2021 NUM cana-3756 171 6 . . PUNCT cana-3756 172 1 [ [ X cana-3756 172 2 11 11 NUM cana-3756 172 3 ] ] PUNCT cana-3756 172 4 l. l. PROPN cana-3756 172 5 chen chen PROPN cana-3756 172 6 and and CCONJ cana-3756 172 7 y. y. PROPN cana-3756 172 8 wang wang PROPN cana-3756 172 9 , , PUNCT cana-3756 172 10 " " PUNCT cana-3756 172 11 mobilenetv3 mobilenetv3 NOUN cana-3756 172 12 for for ADP cana-3756 172 13 efficient efficient ADJ cana-3756 172 14 gender gender NOUN cana-3756 172 15 recognition recognition NOUN cana-3756 172 16 , , PUNCT cana-3756 172 17 " " PUNCT cana-3756 172 18 pattern pattern NOUN cana-3756 172 19 recognit recognit VERB cana-3756 172 20 . . PUNCT cana-3756 172 21 , , PUNCT cana-3756 172 22 vol vol NOUN cana-3756 172 23 . . PROPN cana-3756 172 24 124 124 NUM cana-3756 172 25 , , PUNCT cana-3756 172 26 art art NOUN cana-3756 172 27 . . PUNCT cana-3756 173 1 no no INTJ cana-3756 173 2 . . NOUN cana-3756 174 1 108487 108487 NUM cana-3756 174 2 , , PUNCT cana-3756 174 3 2022 2022 NUM cana-3756 174 4 . . PUNCT cana-3756 175 1 communications communication NOUN cana-3756 175 2 on on ADP cana-3756 175 3 applied apply VERB cana-3756 175 4 nonlinear nonlinear ADJ cana-3756 175 5 analysis analysis NOUN cana-3756 175 6 issn issn NOUN cana-3756 175 7 : : PUNCT cana-3756 175 8 1074 1074 NUM cana-3756 175 9 - - PUNCT cana-3756 175 10 133x 133x NUM cana-3756 175 11 vol vol NOUN cana-3756 175 12 32 32 NUM cana-3756 175 13 no no NOUN cana-3756 175 14 . . PUNCT cana-3756 176 1 8s 8s PROPN cana-3756 176 2 ( ( PUNCT cana-3756 176 3 2025 2025 NUM cana-3756 176 4 ) ) PUNCT cana-3756 176 5 693 693 NUM cana-3756 176 6 https://internationalpubls.com https://internationalpubls.com X cana-3756 177 1 [ [ X cana-3756 177 2 12 12 NUM cana-3756 177 3 ] ] PUNCT cana-3756 177 4 s. s. PROPN cana-3756 177 5 kumar kumar PROPN cana-3756 177 6 , , PUNCT cana-3756 177 7 r. r. PROPN cana-3756 177 8 singh singh PROPN cana-3756 177 9 , , PUNCT cana-3756 177 10 and and CCONJ cana-3756 177 11 m. m. NOUN cana-3756 177 12 vatsa vatsa NOUN cana-3756 177 13 , , PUNCT cana-3756 177 14 " " PUNCT cana-3756 177 15 temporal temporal ADJ cana-3756 177 16 feature feature NOUN cana-3756 177 17 learning learn VERB cana-3756 177 18 for for ADP cana-3756 177 19 gender gender NOUN cana-3756 177 20 recognition recognition NOUN cana-3756 177 21 using use VERB cana-3756 177 22 cnn cnn PROPN cana-3756 177 23 - - PUNCT cana-3756 177 24 rnn rnn NOUN cana-3756 177 25 architecture architecture NOUN cana-3756 177 26 , , PUNCT cana-3756 177 27 " " PUNCT cana-3756 177 28 ieee ieee NOUN cana-3756 177 29 trans tran NOUN cana-3756 177 30 . . PUNCT cana-3756 178 1 biometrics biometric NOUN cana-3756 178 2 , , PUNCT cana-3756 178 3 behav behav NOUN cana-3756 178 4 . . PUNCT cana-3756 178 5 , , PUNCT cana-3756 178 6 identity identity NOUN cana-3756 178 7 sci sci PROPN cana-3756 178 8 . . PROPN cana-3756 178 9 , , PUNCT cana-3756 178 10 vol vol NOUN cana-3756 178 11 . . PROPN cana-3756 178 12 4 4 NUM cana-3756 178 13 , , PUNCT cana-3756 178 14 no no INTJ cana-3756 178 15 . . NOUN cana-3756 178 16 2 2 NUM cana-3756 178 17 , , PUNCT cana-3756 178 18 pp pp ADJ cana-3756 178 19 . . PUNCT cana-3756 179 1 178 178 NUM cana-3756 179 2 - - SYM cana-3756 179 3 189 189 NUM cana-3756 179 4 , , PUNCT cana-3756 179 5 2022 2022 NUM cana-3756 179 6 . . PUNCT cana-3756 180 1 [ [ X cana-3756 180 2 13 13 NUM cana-3756 180 3 ] ] PUNCT cana-3756 180 4 x. x. NOUN cana-3756 180 5 li li PROPN cana-3756 180 6 , , PUNCT cana-3756 180 7 z. z. PROPN cana-3756 180 8 wang wang PROPN cana-3756 180 9 , , PUNCT cana-3756 180 10 and and CCONJ cana-3756 180 11 h. h. PROPN cana-3756 180 12 chen chen PROPN cana-3756 180 13 , , PUNCT cana-3756 180 14 " " PUNCT cana-3756 180 15 vision vision NOUN cana-3756 180 16 transformer transformer NOUN cana-3756 180 17 for for ADP cana-3756 180 18 gender gender NOUN cana-3756 180 19 recognition recognition NOUN cana-3756 180 20 : : PUNCT cana-3756 180 21 a a DET cana-3756 180 22 new new ADJ cana-3756 180 23 perspective perspective NOUN cana-3756 180 24 , , PUNCT cana-3756 180 25 " " PUNCT cana-3756 180 26 ieee ieee NOUN cana-3756 180 27 trans trans PROPN cana-3756 180 28 . . PUNCT cana-3756 180 29 image image NOUN cana-3756 180 30 process process NOUN cana-3756 180 31 . . PUNCT cana-3756 180 32 , , PUNCT cana-3756 180 33 vol vol NOUN cana-3756 180 34 . . PROPN cana-3756 180 35 32 32 NUM cana-3756 180 36 , , PUNCT cana-3756 180 37 pp pp ADJ cana-3756 180 38 . . PUNCT cana-3756 180 39 1856 1856 NUM cana-3756 180 40 - - SYM cana-3756 180 41 1869 1869 NUM cana-3756 180 42 , , PUNCT cana-3756 180 43 2023 2023 NUM cana-3756 180 44 . . PUNCT cana-3756 181 1 [ [ X cana-3756 181 2 14 14 NUM cana-3756 181 3 ] ] X cana-3756 181 4 s. s. PROPN cana-3756 181 5 park park PROPN cana-3756 181 6 and and CCONJ cana-3756 181 7 j. j. PROPN cana-3756 181 8 kim kim PROPN cana-3756 181 9 , , PUNCT cana-3756 181 10 " " PUNCT cana-3756 181 11 efficientnet efficientnet ADJ cana-3756 181 12 optimization optimization NOUN cana-3756 181 13 for for ADP cana-3756 181 14 real real ADJ cana-3756 181 15 - - PUNCT cana-3756 181 16 time time NOUN cana-3756 181 17 gender gender NOUN cana-3756 181 18 recognition recognition NOUN cana-3756 181 19 , , PUNCT cana-3756 181 20 " " PUNCT cana-3756 181 21 pattern pattern NOUN cana-3756 181 22 recognit recognit VERB cana-3756 181 23 . . PUNCT cana-3756 182 1 lett lett PROPN cana-3756 182 2 . . PROPN cana-3756 182 3 , , PUNCT cana-3756 182 4 vol vol NOUN cana-3756 182 5 . . PROPN cana-3756 182 6 168 168 NUM cana-3756 182 7 , , PUNCT cana-3756 182 8 pp pp ADJ cana-3756 182 9 . . PUNCT cana-3756 183 1 41 41 NUM cana-3756 183 2 - - SYM cana-3756 183 3 48 48 NUM cana-3756 183 4 , , PUNCT cana-3756 183 5 2023 2023 NUM cana-3756 183 6 . . PUNCT cana-3756 184 1 [ [ X cana-3756 184 2 15 15 NUM cana-3756 184 3 ] ] X cana-3756 184 4 m. m. NOUN cana-3756 184 5 rodriguez rodriguez PROPN cana-3756 184 6 , , PUNCT cana-3756 184 7 j. j. PROPN cana-3756 184 8 garcia garcia PROPN cana-3756 184 9 , , PUNCT cana-3756 184 10 and and CCONJ cana-3756 184 11 r. r. PROPN cana-3756 184 12 lopez lopez PROPN cana-3756 184 13 , , PUNCT cana-3756 184 14 " " PUNCT cana-3756 184 15 multi multi ADJ cana-3756 184 16 - - ADJ cana-3756 184 17 task task ADJ cana-3756 184 18 learning learn VERB cana-3756 184 19 framework framework NOUN cana-3756 184 20 for for ADP cana-3756 184 21 gender gender NOUN cana-3756 184 22 and and CCONJ cana-3756 184 23 age age NOUN cana-3756 184 24 estimation estimation NOUN cana-3756 184 25 , , PUNCT cana-3756 184 26 " " PUNCT cana-3756 184 27 comput comput NOUN cana-3756 184 28 . . PUNCT cana-3756 185 1 vis vis X cana-3756 185 2 . . PUNCT cana-3756 185 3 image image NOUN cana-3756 185 4 understand understand VERB cana-3756 185 5 . . PUNCT cana-3756 185 6 , , PUNCT cana-3756 185 7 vol vol NOUN cana-3756 185 8 . . PROPN cana-3756 186 1 227 227 NUM cana-3756 186 2 , , PUNCT cana-3756 186 3 art art NOUN cana-3756 186 4 . . PUNCT cana-3756 187 1 no no INTJ cana-3756 187 2 . . NOUN cana-3756 187 3 103594 103594 NUM cana-3756 187 4 , , PUNCT cana-3756 187 5 2023 2023 NUM cana-3756 187 6 . . PUNCT cana-3756 188 1 [ [ X cana-3756 188 2 16 16 NUM cana-3756 188 3 ] ] X cana-3756 188 4 r. r. PROPN cana-3756 188 5 thompson thompson PROPN cana-3756 188 6 , , PUNCT cana-3756 188 7 m. m. PROPN cana-3756 188 8 wilson wilson PROPN cana-3756 188 9 , , PUNCT cana-3756 188 10 and and CCONJ cana-3756 188 11 k. k. PROPN cana-3756 188 12 davis davis PROPN cana-3756 188 13 , , PUNCT cana-3756 188 14 " " PUNCT cana-3756 188 15 lightweight lightweight ADJ cana-3756 188 16 efficientnetv2 efficientnetv2 NOUN cana-3756 188 17 for for ADP cana-3756 188 18 gender gender NOUN cana-3756 188 19 recognition recognition NOUN cana-3756 188 20 , , PUNCT cana-3756 188 21 " " PUNCT cana-3756 188 22 neural neural ADJ cana-3756 188 23 netw netw NOUN cana-3756 188 24 . . PUNCT cana-3756 188 25 , , PUNCT cana-3756 188 26 vol vol NOUN cana-3756 188 27 . . PROPN cana-3756 189 1 157 157 NUM cana-3756 189 2 , , PUNCT cana-3756 189 3 pp pp ADJ cana-3756 189 4 . . PUNCT cana-3756 190 1 28 28 NUM cana-3756 190 2 - - SYM cana-3756 190 3 37 37 NUM cana-3756 190 4 , , PUNCT cana-3756 190 5 2023 2023 NUM cana-3756 190 6 . . PUNCT cana-3756 191 1 [ [ X cana-3756 191 2 17 17 NUM cana-3756 191 3 ] ] X cana-3756 191 4 c. c. PROPN cana-3756 191 5 martinez martinez PROPN cana-3756 191 6 and and CCONJ cana-3756 191 7 d. d. PROPN cana-3756 191 8 garcia garcia PROPN cana-3756 191 9 , , PUNCT cana-3756 191 10 " " PUNCT cana-3756 191 11 feature feature NOUN cana-3756 191 12 fusion fusion NOUN cana-3756 191 13 techniques technique NOUN cana-3756 191 14 for for ADP cana-3756 191 15 robust robust ADJ cana-3756 191 16 gender gender NOUN cana-3756 191 17 recognition recognition NOUN cana-3756 191 18 , , PUNCT cana-3756 191 19 " " PUNCT cana-3756 191 20 ieee ieee NOUN cana-3756 191 21 trans tran NOUN cana-3756 191 22 . . PUNCT cana-3756 191 23 pattern pattern PROPN cana-3756 191 24 anal anal PROPN cana-3756 191 25 . . PUNCT cana-3756 192 1 mach mach PROPN cana-3756 192 2 . . PUNCT cana-3756 193 1 intell intell PROPN cana-3756 193 2 . . PUNCT cana-3756 194 1 , , PUNCT cana-3756 194 2 vol vol NOUN cana-3756 194 3 . . PROPN cana-3756 195 1 45 45 NUM cana-3756 195 2 , , PUNCT cana-3756 195 3 no no INTJ cana-3756 195 4 . . NOUN cana-3756 195 5 8 8 NUM cana-3756 195 6 , , PUNCT cana-3756 195 7 pp pp ADJ cana-3756 195 8 . . PUNCT cana-3756 196 1 9234 9234 NUM cana-3756 196 2 - - SYM cana-3756 196 3 9246 9246 NUM cana-3756 196 4 , , PUNCT cana-3756 196 5 2023 2023 NUM cana-3756 196 6 . . PUNCT cana-3756 197 1 [ [ X cana-3756 197 2 18 18 NUM cana-3756 197 3 ] ] PUNCT cana-3756 197 4 j. j. PROPN cana-3756 197 5 wilson wilson PROPN cana-3756 197 6 , , PUNCT cana-3756 197 7 a. a. NOUN cana-3756 197 8 brown brown PROPN cana-3756 197 9 , , PUNCT cana-3756 197 10 and and CCONJ cana-3756 197 11 r. r. PROPN cana-3756 197 12 smith smith PROPN cana-3756 197 13 , , PUNCT cana-3756 197 14 " " PUNCT cana-3756 197 15 ensemble ensemble ADJ cana-3756 197 16 methods method NOUN cana-3756 197 17 for for ADP cana-3756 197 18 improved improved ADJ cana-3756 197 19 gender gender NOUN cana-3756 197 20 recognition recognition NOUN cana-3756 197 21 , , PUNCT cana-3756 197 22 " " PUNCT cana-3756 197 23 pattern pattern NOUN cana-3756 197 24 recognit recognit VERB cana-3756 197 25 . . PUNCT cana-3756 197 26 , , PUNCT cana-3756 197 27 vol vol NOUN cana-3756 197 28 . . PROPN cana-3756 197 29 136 136 NUM cana-3756 197 30 , , PUNCT cana-3756 197 31 art art NOUN cana-3756 197 32 . . PUNCT cana-3756 198 1 no no INTJ cana-3756 198 2 . . NOUN cana-3756 198 3 109285 109285 NUM cana-3756 198 4 , , PUNCT cana-3756 198 5 2023 2023 NUM cana-3756 198 6 . . PUNCT cana-3756 199 1 [ [ X cana-3756 199 2 19 19 NUM cana-3756 199 3 ] ] X cana-3756 199 4 y. y. PROPN cana-3756 199 5 zhao zhao PROPN cana-3756 199 6 , , PUNCT cana-3756 199 7 x. x. PROPN cana-3756 199 8 liu liu PROPN cana-3756 199 9 , , PUNCT cana-3756 199 10 and and CCONJ cana-3756 199 11 h. h. PROPN cana-3756 199 12 wang wang PROPN cana-3756 199 13 , , PUNCT cana-3756 199 14 " " PUNCT cana-3756 199 15 self self NOUN cana-3756 199 16 - - PUNCT cana-3756 199 17 attention attention NOUN cana-3756 199 18 mechanisms mechanism NOUN cana-3756 199 19 in in ADP cana-3756 199 20 mobile mobile ADJ cana-3756 199 21 networks network NOUN cana-3756 199 22 for for ADP cana-3756 199 23 gender gender NOUN cana-3756 199 24 recognition recognition NOUN cana-3756 199 25 , , PUNCT cana-3756 199 26 " " PUNCT cana-3756 199 27 ieee ieee NOUN cana-3756 199 28 access access NOUN cana-3756 199 29 , , PUNCT cana-3756 199 30 vol vol NOUN cana-3756 199 31 . . PROPN cana-3756 199 32 11 11 NUM cana-3756 199 33 , , PUNCT cana-3756 199 34 pp pp ADJ cana-3756 199 35 . . PUNCT cana-3756 200 1 54321 54321 NUM cana-3756 200 2 - - SYM cana-3756 200 3 54334 54334 NUM cana-3756 200 4 , , PUNCT cana-3756 200 5 2023 2023 NUM cana-3756 200 6 . . PUNCT cana-3756 201 1 [ [ X cana-3756 201 2 20 20 NUM cana-3756 201 3 ] ] PUNCT cana-3756 201 4 s. s. PROPN cana-3756 201 5 kim kim PROPN cana-3756 201 6 and and CCONJ cana-3756 201 7 j. j. PROPN cana-3756 201 8 lee lee PROPN cana-3756 201 9 , , PUNCT cana-3756 201 10 " " PUNCT cana-3756 201 11 hybrid hybrid ADJ cana-3756 201 12 efficientnet efficientnet ADJ cana-3756 201 13 - - PUNCT cana-3756 201 14 transformer transformer NOUN cana-3756 201 15 architecture architecture NOUN cana-3756 201 16 for for ADP cana-3756 201 17 gender gender NOUN cana-3756 201 18 recognition recognition NOUN cana-3756 201 19 , , PUNCT cana-3756 201 20 " " PUNCT cana-3756 201 21 neural neural ADJ cana-3756 201 22 comput comput NOUN cana-3756 201 23 . . PUNCT cana-3756 202 1 appl appl PROPN cana-3756 202 2 . . PROPN cana-3756 202 3 , , PUNCT cana-3756 202 4 early early ADJ cana-3756 202 5 access access NOUN cana-3756 202 6 , , PUNCT cana-3756 202 7 pp pp ADJ cana-3756 202 8 . . PUNCT cana-3756 203 1 1 1 NUM cana-3756 203 2 - - SYM cana-3756 203 3 12 12 NUM cana-3756 203 4 , , PUNCT cana-3756 203 5 2024 2024 NUM cana-3756 203 6 . . PUNCT