Facial Expression Recognition Using Transfer Learning on Deep Convolutional Network

被引：2
|
作者：
Hablani, Ramchand [1 ]
机构：
[1] Shri Ramdeobaba Coll Engn & Management, Nagpur, Maharashtra, India
来源：
BIOSCIENCE BIOTECHNOLOGY RESEARCH COMMUNICATIONS | 2020年 / 13卷 / 14期
关键词：
FACIAL EXPRESS ION RECOGNITION; ALEXNET; VGG19; TRANSFER LEARNING; FEATURE EXTRACTION;
D O I：
10.21786/bbrc/13.14/44
中图分类号：
Q81 [生物工程学（生物技术）]; Q93 [微生物学];
学科分类号：
071005 ; 0836 ; 090102 ; 100705 ;
摘要：
A novel method is proposed for facial expression recognition. We have implemented two techniques for automatic facial expression recognition. First, we applied transfer learning to AlexNet, and VGG19 for classification. Second, we used AlexNet and Vgg19 for feature extraction and cascaded it with an SVM for classification. We achieved 86.11% accuracy with AlexNet and 94.44% with AlexNet-SVM cascade. We also achieved 94.44% accuracy with VGG19 and 86.11 with VGG19-SVM cascade. We used JAFFE Data Set to train our four models. Our system achieves an improvement in accuracy for JAFFE Data Set.
引用
收藏
页码：185 / 188
页数：4
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