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Low-resolution face recognition with single sample per person

  • Published:2017-12 Issue: Volume:141 Page:144-157
  • ISSN:0165-1684
  • Container-title:Signal Processing
  • language:en
  • Short-container-title:Signal Processing

Author:

Chu Yongjie,Ahmad Touqeer,Bebis George,Zhao Lindu

Funder

National Natural Science Foundation of China

National Key Technology R&D Program of China

Postgraduate Research & Practice Innovation Program of Jiangsu Province

China Scholarship Council

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software,Control and Systems Engineering

Reference44 articles.

1. Recognizing partially occluded faces from a single sample per class using string-based matching;Chen,2010

2. Discriminative multimanifold analysis for face recognition from a single training sample per person;Lu;Pattern Anal. Mach. Intell. IEEE Trans.,2013

3. Double linear regressions for single labeled image per person face recognition;Yin;Pattern Recognit.,2014

4. Neither global nor local: regularized patch-based representation for single sample per person face recognition;Gao;Int. J. Comput. Vision,2015

5. Making FLDA applicable to face recognition with one sample per person;Chen;Pattern Recognit.,2004

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