id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
cuesj-1203	Husari, Fatimatelbatoul M.; Assaad, Mohammad A.	Intelligent Handwritten Identification Using Novel Hybrid Convolutional Neural Networks – Long-short-term Memory Architecture	2024	5	.pdf	application/pdf	3186	146	40	This XN vector represents the main features extracted by CNN layer and is directly inputted into LSTM layer as described in the following analysis equation: Figure 1: Basic structure of long-short-term memory model Husari and Assaad: Intelligent Handwritten Identification Using Novel Hybrid CNN-LSTM model 101 http://journals.cihanuniversity.edu.iq/index.php/cuesj CUESJ 2024, 8 (2): 99-103 The initial step is deciding which information will be excluded from the previous cell state Ct-1 using forget gate f1. The outcomes proved that the learned meaningful features by CNN network are efficient and superior in accuracy 98% accuracy compared to SVM, decision tree, and random forest (94%, 74%, and 89%), respectively.	cache/cuesj-1203.pdf	txt/cuesj-1203.txt