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  • 标题:A Novel Solution to Test Face Recognition Methods on the Training Data Set
  • 本地全文:下载
  • 作者:Weiwei Wu
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2015
  • 卷号:8
  • 期号:9
  • 页码:21-30
  • DOI:10.14257/ijsip.2015.8.9.03
  • 出版社:SERSC
  • 摘要:In modern life, we need better techniques based on biometric features recognition such as face recognition, fingerprint recognition and iris recognition. We present a method which can be used for face recognition or verification applications. The method can solve the problem that when the number of data categories is large and each number of the category used for training is small. As the conventional four stages, face detection, face alignment, face representation and face classification, we propose a Siamese architecture especially for the representation stage and use a one-against-one support vector machine for the classification stage. LFW dataset is used for training and testing which gets a considerable result. And we also test our system on other face dataset, which has a high accuracy on the recognition
  • 关键词:face recognition; face verification; Siamese convolutional neural network; ; support vector machine
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