Adaptive Histogram Normalization based Loss Function in Deep Learning Algorithm for Face Recognition

被引：2
|
作者：
Lin, Ren-Shin [1 ]
Lee, Pei-Jun [1 ]
Bui, Trong-An [1 ]
机构：
[1] Natl Chi Nan Univ, Elect Engn Dept, Puli Township, Taiwan
来源：
2019 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN (ICCE-TW) | 2019年
关键词：
artificial intelligence; deep learning; neural network; face recognition;
D O I：
10.1109/icce-tw46550.2019.8991751
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
To improve the recognition accuracy and to solve the overfitting problem of traditional face recognition methods, this paper proposed an adaptive histogram normalization algorithm to reduce brightness effect in training data and designing loss function. The proposed algorithm can adaptive adjustment training images and inference parameters based on the real-time captured images data. In experimental results, the proposed algorithm has higher accuracy than other algorithms and has higher testing accuracy to improve overfitting.
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收藏
页数：2
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