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Learning Gabor layer for edge detection network

delete2025-07-04
delete0
PRE
AI
H
Haihua Ding
H
Huang, Sihan
C
Chuan Lin
DOI：10.1016/j.dsp.2025.105438delete
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Abstract

Abstract

En 中文
• Propose novel LGLNet model for high-accuracy edge detection with fewer parameters and lower computational complexity. • Design Learning Gabor Layer (LGL) with 150 params. It generates position-specific filters for efficient extraction of fine edge features. • Use pixel-difference gradients to dynamically compute Gabor angles per spatial location in real-time.

Journal

Signal Processing cover
Signal Processing
IF:
3.6
Papers:
9.9K
Citations:
1.7W

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