首页> 外文会议>International Conference of Soft Computing and Pattern Recognition >Facial Features Classification using The Temporal Correlation Matrix Memory (TCMML)
【24h】

Facial Features Classification using The Temporal Correlation Matrix Memory (TCMML)

机译:面部特征使用时间相关矩阵内存(TCMML)进行分类

获取原文

摘要

This paper examines the motivation and concepts of dynamic encoders (for binary neural networks) introduced by Shah in the author's RASC 2004 and 2006 conference papers [1], [2]. Further to this, the paper extends the claims made by Shah et al. in their UCNN2007 conference paper [3] about dynamic encoders and offers a different understanding to using dynamic encoders. In addition the paper also derives the Improved Correlation Matrix Memory (CMML) (first introduced by Shah et al.) via practical considerations (as opposed to a theoretical concept), supplies a theorem that provides the missing justification over the use of the improved adjective, before finally enhancing the CMML into the 'Improved' Temporal Correlation Matrix Memory (TCMML) together with a brief discussion on an application for recognising facial features.
机译:本文研究了Shah在作者Rasc 2004和2006年会议论文中引入的动态编码(用于二元神经网络)的动力和概念[1],[2]。此外,本文延伸了Shah等人制造的权利要求。在他们的UCN2007会议论文[3]关于动态编码器并提供不同的理解,使用动态编码器。此外,本文还衍生出改进的相关矩阵存储器(CMML)(Shah等人首次由Shah等人推出)通过实际考虑(与理论概念相反),提供了一个定理,该定理提供了在使用改进的形容词上使用的缺失理由在最后将CMML增强到“改进的”时间相关矩阵存储器(TCMML)之前,以及关于识别面部特征的应用程序的简要讨论。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号