电子发烧友App

硬声App

0
  • 聊天消息
  • 系统消息
  • 评论与回复
登录后你可以
  • 下载海量资料
  • 学习在线课程
  • 观看技术视频
  • 写文章/发帖/加入社区
会员中心
创作中心

完善资料让更多小伙伴认识你,还能领取20积分哦,立即完善>

3天内不再提示
电子发烧友网>电子资料下载>电子论文>模拟数字论文>deepid3:非常深的神经网络的人脸识别深度算法的网络架构

deepid3:非常深的神经网络的人脸识别深度算法的网络架构

2017-10-17 | pdf | 4528KB | 次下载 | 免费

资料介绍

人脸识别 深度算法网络架构 恨偶参考价值

  Using deep neural networks to learn effective feature representations has become popular in face recognition [12, 20, 17, 22, 14, 13, 18, 21, 19, 15]。 With better deep network architectures and supervisory methods, face recognition accuracy has been boosted rapidly in recent years. In particular, a few noticeable face representation learning techniques are evolved recently. An early effort of learning deep face representation in a supervised way was to employ face verification as the supervisory signal [12], which required classifying a pair of training images as being the same person or not. It greatly reduced the intra-personal variations in the face representation. Then learning discriminative deep face representation through large-scale face identity classification (face identification) was proposed by DeepID [14] and DeepFace [17, 18]。 By classifying training images into a large amount of identities, the last hidden layer of deep neural networks would form rich identity-related features. With this technique, deep learning got close to human performance for the first time on tightly cropped face images of the extensively evaluated LFW face verification dataset [6]。 However, the learned face representation could also contain significant intrapersonal variations. Motivated by both [12] and [14], an approach of learning deep face representation by joint face identification-verification was proposed in DeepID2 [13] and was further improved in DeepID2+ [15]。 Adding verification supervisory signals significantly reduced intrapersonal variations, leading to another significant improvement on face recognition performance. Human face verification accuracy on the entire face images of LFW was surpassed finally [13, 15]。 Both GoogLeNet [16] and VGG [10] ranked in the top in general image classification in ILSVRC 2014. This motivates us to investigate whether the superb learning capacity brought by very deep net structures can also benefit face recognition.

下载该资料的人也在下载 下载该资料的人还在阅读
更多 >

评论

查看更多

下载排行

本周

  1. 1TC358743XBG评估板参考手册
  2. 1.36 MB  |  330次下载  |  免费
  3. 2开关电源基础知识
  4. 5.73 MB  |  11次下载  |  免费
  5. 3嵌入式linux-聊天程序设计
  6. 0.60 MB  |  3次下载  |  免费
  7. 4DIY动手组装LED电子显示屏
  8. 0.98 MB  |  3次下载  |  免费
  9. 5基于FPGA的C8051F单片机开发板设计
  10. 0.70 MB  |  2次下载  |  免费
  11. 651单片机窗帘控制器仿真程序
  12. 1.93 MB  |  2次下载  |  免费
  13. 751单片机大棚环境控制器仿真程序
  14. 1.10 MB  |  2次下载  |  免费
  15. 8基于51单片机的RGB调色灯程序仿真
  16. 0.86 MB  |  2次下载  |  免费

本月

  1. 1OrCAD10.5下载OrCAD10.5中文版软件
  2. 0.00 MB  |  234315次下载  |  免费
  3. 2555集成电路应用800例(新编版)
  4. 0.00 MB  |  33566次下载  |  免费
  5. 3接口电路图大全
  6. 未知  |  30323次下载  |  免费
  7. 4开关电源设计实例指南
  8. 未知  |  21549次下载  |  免费
  9. 5电气工程师手册免费下载(新编第二版pdf电子书)
  10. 0.00 MB  |  15349次下载  |  免费
  11. 6数字电路基础pdf(下载)
  12. 未知  |  13750次下载  |  免费
  13. 7电子制作实例集锦 下载
  14. 未知  |  8113次下载  |  免费
  15. 8《LED驱动电路设计》 温德尔著
  16. 0.00 MB  |  6656次下载  |  免费

总榜

  1. 1matlab软件下载入口
  2. 未知  |  935054次下载  |  免费
  3. 2protel99se软件下载(可英文版转中文版)
  4. 78.1 MB  |  537798次下载  |  免费
  5. 3MATLAB 7.1 下载 (含软件介绍)
  6. 未知  |  420027次下载  |  免费
  7. 4OrCAD10.5下载OrCAD10.5中文版软件
  8. 0.00 MB  |  234315次下载  |  免费
  9. 5Altium DXP2002下载入口
  10. 未知  |  233046次下载  |  免费
  11. 6电路仿真软件multisim 10.0免费下载
  12. 340992  |  191186次下载  |  免费
  13. 7十天学会AVR单片机与C语言视频教程 下载
  14. 158M  |  183279次下载  |  免费
  15. 8proe5.0野火版下载(中文版免费下载)
  16. 未知  |  138040次下载  |  免费