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Sparse non-negative transition subspace learning for image classification

  • Published:2021-06 Issue: Volume:183 Page:107988
  • ISSN:0165-1684
  • Container-title:Signal Processing
  • language:en
  • Short-container-title:Signal Processing

Author:

Chen Zhe,Wu Xiao-Jun,Cai Yu-Hong,Kittler Josef

Publisher

Elsevier BV

Subject

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

Reference58 articles.

1. Representation learning: a review and new perspectives;Bengio;IEEE Trans. Pattern Anal. Mach. Intell.,2013

2. Discriminative block-diagonal representation learning for image recognition;Zhang;IEEE Trans. Neural Netw. Learn. Syst.,2017

3. Robust regression;Huang;IEEE Trans. Pattern Anal. Mach. Intell.,2015

4. The collinearity problem in linear regression. the partial least squares (PLS) approach to generalized inverses;Wold;SIAM J. Sci. Stat. Comput.,1984

5. Face recognition using kernel ridge regression;An,2007

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1. Robust Supervised Spline Embedding;IEEE Transactions on Neural Networks and Learning Systems;2024

2. Inter-class Sparsity Based Non-negative Transition Sub-space Learning;Pattern Recognition and Computer Vision;2023-12-24

3. Dual Discriminative Low-Rank Projection Learning for Robust Image Classification;IEEE Transactions on Circuits and Systems for Video Technology;2023-12

4. Adaptive Submanifold-Preserving Sparse Regression for Feature Selection And Multiclass Classification;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

5. Unconstrained neighbor selection for minimum reconstruction error-based K-NN classifiers;Complex & Intelligent Systems;2023-04-03
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