Apr 6, 2022 · Our proposed method tries to find robust features by learning the structure of residues. That is, we regard residues as a measurement of input data and its low ...
In this paper, a robust low-rank representation via residual projection is proposed. Different from traditional low-rank representation methods, which regard ...
Jan 28, 2022 · In this paper, a robust low-rank representation via residual projection is proposed. Different from traditional low-rank representation methods, ...
Robust low-rank representation via residual projection for image classification ; Journal: Knowledge-Based Systems, 2022, p. 108230 ; Publisher: Elsevier BV.
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Bibliographic details on Robust low-rank representation via residual projection for image classification.
By incorporating sparse regularization, LMVSC-Sparse can effectively handle outlier sensitivity, which is a common challenge in traditional MVSC methods relying ...
Jun 26, 2023 · This paper proposes a novel method named ESL-LRR, which preserves image edges by finding image projections from low-rank residuals.
Feb 7, 2023 · Traditional low-rank methods overlook residuals as corruptions, but we discovered that low-rank residuals actually keep image edges together ...
2) The proposed ESL-LRR preserves the image edges by pursuing robust image projections from low-rank residu- als through a manifold learning framework. In this ...
Traditional low-rank methods overlook residuals as corruptions, but we discovered that low-rank residuals actually keep image edges together with corrupt ...