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  • 标题:An Enhancement of Deep Face Technique Using Neural Network
  • 本地全文:下载
  • 作者:Gurpreet Kaur ; Sukhvir Kaur
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2016
  • 卷号:9
  • 期号:8
  • 页码:285-294
  • 出版社:SERSC
  • 摘要:Face recognition is an assignment that people perform routinely and easily in their everyday lives. The most recent decade has seen a pattern towards an inexorably universal nature, where compelling and minimal effort registering frameworks are, no doubt coordinated into cell telephones, autos, therapeutic instruments and very nearly every part of our lives. In the previous work, few researchers have focused on detection of face using some methodology. In this research paper, the face recognition system proposed the Detection time, false negative in missed faces and optimality of the face. This proposed research work has been focused on optimality features of the neural network for the face images and detection time. In this paper, we have applied the neural network for three parameters such – detection time, false acceptance rate, successful rates, no. of failure, and cross correlation. Our proposed parameters provide better result as compared to the previous methodology.
  • 关键词:Face recognition; False acceptance rate; Cross Correlation; Neural ;networ;k;Feature
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