Apr 22, 2020 · In this paper, a novel sparse representation that learns double weights through data augmentation is proposed for robust image classification.
The first weight combines the two coefficients solved by l1 and l2 regularizations to obtain a more discriminative representation, while the second weight ...
In this paper, a novel sparse representation that learns double weights through data augmentation is proposed for robust image classification.
Detailed Record. Title: Learning double weights via data augmentation for robust sparse and collaborative representation-based classification. Language: English
Apr 1, 2020 · In this paper, a novel sparse representation that learns double weights through data augmentation is proposed for robust image classification.
Learning double weights via data augmentation for robust sparse and collaborative representation-based classification. https://doi.org/10.1007/s11042-020 ...
Learning double weights via data augmentation for robust sparse and ...
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Image classification is a hot technique applied in many multimedia systems, where both l and l regularizations have shown potential for robust sparse ...
Learning double weights via data augmentation for robust sparse and collaborative representation-based classification. Article. Full-text available. Aug 2020.
Learning double weights via data augmentation for robust sparse and collaborative representation-based classification ; CiteScore. 7.20 ; 自引率. 16.70% ; 发文量.
Dual sparse learning via data augmentation for robust facial image classification · A new discriminative collaborative representation-based classification method ...
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