id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
aiti-6939	Chen, Kun-Yi; Chang, Chi-Yu ; Tsai, Zhi-Ren ; Lee, Chun-Ting ; Shae, Zon-Yin 	Tea Verification Using Triplet Loss Convolutional Network	2021	14	.pdf	application/pdf	5106	248	58	5 Tea sub-images that belong to the same image Fig. 6 t-SNE plot of two tea classes using the five most significant color information The first observation using model visualization algorithms shows that the feature property between tea image and traditional image are different, i.e., distributed objects’ feature property (tea images) versus non-distributed objects’ feature property (traditional images). In the experiment, instead of using traditional deep learning training approach for local feature of tea images, an innovative image verification approach is proposed to learn the global feature of tea images by integrating the distributed tea leaves’ features of all tea sub-images and using a majority voting mechanism to do classification.	cache/aiti-6939.pdf	txt/aiti-6939.txt