全部版块 我的主页
论坛 计量经济学与统计论坛 五区 计量经济学与统计软件 winbugs及其他软件专版
1743 9
2016-01-18
悬赏 1 个论坛币 未解决


https://www.crcpress.com/Face-Detection-and-Recognition-Theory-and-Practice/Datta-Datta-Banerjee/9781482226546?source=igodigital

Features
  • Explains the theory and practice of face detection and recognition systems currently in vogue
  • Offers a general review of the available face detection and recognition methods, as well as an indication of future research using cognitive neurophysiology
  • Provides a single source for cutting-edge information on the major approaches, algorithms, and technologies used in automated face detection and recognition
Summary

Face detection and recognition are the nonintrusive biometrics of choice in many security applications. Examples of their use include border control, driver’s license issuance, law enforcement investigations, and physical access control.

Face Detection and Recognition: Theory and Practice elaborates on and explains the theory and practice of face detection and recognition systems currently in vogue. The book begins with an introduction to the state of the art, offering a general review of the available methods and an indication of future research using cognitive neurophysiology. The text then:

  • Explores subspace methods for dimensionality reduction in face image processing, statistical methods applied to face detection, and intelligent face detection methods dominated by the use of artificial neural networks
  • Covers face detection with colour and infrared face images, face detection in real time, face detection and recognition using set estimation theory, face recognition using evolutionary algorithms, and face recognition in frequency domain
  • Discusses methods for the localization of face landmarks helpful in face recognition, methods of generating synthetic face images using set estimation theory, and databases of face images available for testing and training systems
  • Features pictorial descriptions of every algorithm as well as downloadable source code (in MATLAB®/PYTHON) and hardware implementation strategies with code examples
  • Demonstrates how frequency domain correlation techniques can be used supplying exhaustive test results

二维码

扫码加我 拉你入群

请注明:姓名-公司-职位

以便审核进群资格,未注明则拒绝

全部回复
2016-1-18 01:49:22
复制代码
二维码

扫码加我 拉你入群

请注明:姓名-公司-职位

以便审核进群资格,未注明则拒绝

2016-1-18 01:51:07
复制代码
二维码

扫码加我 拉你入群

请注明:姓名-公司-职位

以便审核进群资格,未注明则拒绝

2016-1-18 01:52:51
复制代码
二维码

扫码加我 拉你入群

请注明:姓名-公司-职位

以便审核进群资格,未注明则拒绝

2016-1-18 01:53:48
复制代码
二维码

扫码加我 拉你入群

请注明:姓名-公司-职位

以便审核进群资格,未注明则拒绝

2016-1-18 01:55:57

Principal Component Analysis using Python

复制代码
二维码

扫码加我 拉你入群

请注明:姓名-公司-职位

以便审核进群资格,未注明则拒绝

点击查看更多内容…
相关推荐
栏目导航
热门文章
推荐文章

说点什么

分享

扫码加好友,拉您进群
各岗位、行业、专业交流群