1 code implementation • 23 Jan 2022 • He-Feng Yin, Xiao-Jun Wu, Xiaoning Song
The second order image gradient orientations (SOIGO) can mitigate the adverse effect of noises in face images.
no code implementations • 17 Aug 2021 • Donglin Zhang, Xiao-Jun Wu, He-Feng Yin, Josef Kittler
To this end, we develop a novel Multiple hash cOdes jOint learNing method (MOON) for cross-media retrieval.
1 code implementation • 10 Jul 2020 • He-Feng Yin, Xiao-Jun Wu, Zhen-Hua Feng, Josef Kittler
Moreover, ANCR introduces an affine constraint to better represent the data from affine subspaces.
no code implementations • 9 Feb 2020 • Zi-Qi Li, Jun Sun, Xiao-Jun Wu, He-Feng Yin
Recent years have witnessed the success of dictionary learning (DL) based approaches in the domain of pattern classification.
no code implementations • 21 Jan 2020 • Ning Yuan, Xiao-Jun Wu, He-Feng Yin
The method CSKDA needs to choose a proper kernel function through many experiments, while the new method could learn the kernel from data automatically which could save a lot of time and have the robust performance.
1 code implementation • 20 Jan 2020 • Zi-Qi Li, Jun Sun, Xiao-Jun Wu, He-Feng Yin
Firstly, the coefficients of the test sample are obtained by SRC and CCRC, respectively.
1 code implementation • 27 Dec 2019 • Xiao-Yun Cai, He-Feng Yin
In order to enhance the performance of image recognition, a sparsity augmented probabilistic collaborative representation based classification (SA-ProCRC) method is presented.
no code implementations • 23 Dec 2019 • Xing Liu, Xiao-Jun Wu, Zhen Liu, He-Feng Yin
The technology of face recognition has made some progress in recent years.
no code implementations • 21 Dec 2019 • Wen-Jin Fu, Xiao-Jun Wu, He-Feng Yin, Wen-Bo Hu
Recently, sparse subspace clustering has been a valid tool to deal with high-dimensional data.
no code implementations • 17 Dec 2019 • Wen Zhao, Xiao-Jun Wu, He-Feng Yin, Zi-Qi Li
Collaborative representation based classification (CRC) method is exploited in our proposed method which has closed-form solution.
no code implementations • 10 Dec 2019 • Pei Xie, He-Feng Yin, Xiao-Jun Wu
Face recognition remains a hot topic in computer vision, and it is challenging to tackle the problem that both the training and testing images are corrupted.
1 code implementation • 6 Dec 2019 • He-Feng Yin, Xiao-Jun Wu, Josef Kittler
First, a low-rank representation is introduced to handle the possible contamination of the training as well as test data.
no code implementations • 23 Nov 2019 • He-Feng Yin, Xiao-Jun Wu, Josef Kittler, Zhen-Hua Feng
To counteract this problem, we propose an approach that learns Representation with Block-Diagonal Structure (RBDS) for robust image recognition.
1 code implementation • 22 Nov 2019 • He-Feng Yin, Xiao-Jun Wu
Representation based classification method (RBCM) remains one of the hottest topics in the community of pattern recognition, and the recently proposed non-negative representation based classification (NRC) achieved impressive recognition results in various classification tasks.
1 code implementation • 22 Nov 2019 • He-Feng Yin, Xiao-Jun Wu, Su-Gen Chen
In this paper, we propose a locality constraint dictionary learning with support vector discriminative term (LCDL-SV), in which the locality information is preserved by employing the graph Laplacian matrix of the learned dictionary.