We have presented a supervised sparse discriminant projection learning algorithm which preforms subspace learning and feature selection simultaneously. The ...
In this section, we introduce the proposed method called sparse approximation to discriminant projection learning. The main content will be separated into the ...
Extensive experiments on all sorts of image classification tasks, such as face recognition, palmprint recognition, object categorization and texture ...
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Sparse approximation to discriminant projection learning and application to image classification. R. Yu-Feng Yua, Chuan-Xian Renb, Min Jiangc, Man-Yu Sunb ...
Oct 23, 2012 · In this paper, we propose a novel framework called sparse 2-D projections (S2DP) for image feature extraction. Different from the existing 2-D ...
This paper presents a new dictionary learning model to improve sparse representation for image classification, which targets at learning a class-specific ...
In this paper, we propose a discriminative projection and representation-based classification (DPRC) method to enhance the discriminant ability of the SRC.
Sep 10, 2019 · To address this problem, we propose a sparse-adaptive hypergraph discriminant analysis (SAHDA) method to obtain the embedding features of the ...
Missing: approximation | Show results with:approximation
Apr 26, 2018 · This model denotes that the "ideal projection" of a sample point x on the hyper-space H may be gained by iteratively computing the projection of ...
Sparse approximation to discriminant projection learning and application to image classification ... learning method called sparse tensor discriminant analysis ...