.png){kind=icon}
返回
Efficient k-class approach for face recognition
.png){kind=icon}
PRE
AI
DOI：10.1016/j.compeleceng.2015.03.031.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this research work, a new k-class approach for efficient and accurate face recognition called kCAFRe is established. The kCAFRe system has three stages: preprocessing, training, and testing. In the training phase, four reference pictures (classes) are constructed for each person. During testing, the correlation coefficient (CC) is calculated between the picture under test and each of the reference pictures. For each person, one accredited class is chosen. Subsequently, the accredited class for the person with the highest CC is selected. Results were given for four image databases. A recognition ratio of 97% has been obtained for the Libor Spacek's set. (C) 2015 Elsevier Ltd. All rights reserved.
Keyword:
Face detection
Face recognition
Recognition rate
Self-organizing-maps
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
4.9
论文数:
6.7K
被引数:
1.3W
机构
引用论文
African swine fever virus-like integrated elements in a soft tick genome – an ancient virus vector arms race?非洲猪瘟病毒样整合元件在软蜱基因组中——一场古老的病毒媒介军备竞赛？.png)
OAAI
IF0
OAAI分享收藏分享收藏分享收藏Quantifying the Phenomenology of Ghostly Episodes: Part I - Need for a Standard Operationalization
PREAI
分享收藏分享收藏
查看更多内容