A constrained generative model applied to face detection

被引：0
|
作者：
Feraud, R [1 ]
Bernier, O [1 ]
Collobert, D [1 ]
机构：
[1] FRANCE TELECOM,CNET,TECHNOPOLE ANTICIPA,TNT,RIO,LAB,F-22307 LANNION,FRANCE
来源：
NEURAL PROCESSING LETTERS | 1997年 / 5卷 / 02期
关键词：
autoencoder; face detection; information theory; neural network;
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：
A generative neural network model, constrained by non-face examples chosen by an iterative algorithm, is applied to fact: detection. To improve the generalization ability of the model, another constraint based on the minimum description length is added. This model is tested and compared with another state-of-the-art face detection system on a large image test set collected at CMU.
引用
收藏
页码：73 / 81
页数：9
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