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Flexible competitive weighted nonnegative representation method for classification

delete2025-07-12
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PRE
AI
李子奇 cover
李子奇 (Ziqi Li)
H
Hongcheng Song
郭亭亭 cover
郭亭亭 (Tingting Guo)
Z
Zhi-Lin Chen
孙军 (Jun Sun)
DOI:10.1016/j.eswa.2025.128991delete
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Abstract

Abstract

En 中文
• A novel improved nonnegative representation method named FCWNR is proposed. • Two constraints are integrated to form discriminative representation coefficients. • A key flexible factor is introduced to bridge and coordinate the two constraint terms. • FCWNR shows superior performance on public image classification datasets.

Journal

Expert Systems with Applications cover
Expert Systems with Applications
IF:
7.5
Papers:
2.9W
Citations:
10.2W

Organization

No organization information available