id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_b76j4e4nu5h7lgcro2holgdhqy	Siming Zheng	3D texture-based face recognition system using fine-tuned deep residual networks	2019	21	.pdf	application/pdf	8882	885	59	dataset, as the fine-tuned ResNet deep neural network layers are increased, the best TopKeywords 3D textures, Face recognition system, Histogram of oriented gradients features, Deep Extracting better features are a key process for 3D face recognition 3D texture-based face recognition system using finetuned deep residual networks. developed a residual neural network model base on ResNet for the 3D face recognition This model is fine-tuned with different depths using HOG featured 3D face textures. We trained fine-tuned ResNet models with different depths using HOG based 3D texture representative features of face are extracted from the fine-tuned VGGNet model. HOG features and SVM classifier-based face recognition algorithm is for extracting the HOG features based on 3D face texture images. processing of HOG feature extraction for 3D face image is shown in Figs. layer through the fine-tuning method on 3D face texture recognition research with high	./cache/work_b76j4e4nu5h7lgcro2holgdhqy.pdf	./txt/work_b76j4e4nu5h7lgcro2holgdhqy.txt