Face Recognition with Improved Deep Belief Networks

被引：0

作者：

Fan, Rong ^{[1
]}

Hu, Wenxin ^{[1
]}

机构：

[1] East China Normal Univ, Shanghai, Peoples R China

来源：

2017 13TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD) | 2017年

关键词：

Deep Learning; Deep Belief Networks; Face Recognition; Dropout;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Deep learning techniques have become the state-of-theart approach for classification in artificial intelligence, and applied in many widespread subjects. Deep Belief Networks ( DBNs) are one of the most successful models. DBNs consist of many layers of hidden factors along with a greedy layer-wise unsupervised learning algorithm. In our paper, we brought forward an approach to face recognition based on dropout DBNs, which made good performances on small training sets.

引用

页数：5

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