PMSA-DyTr: Prior-Modulated and Semantic-Aligned Dynamic Transformer for Strip Steel Defect Detection
Author:
Affiliation:
1. Central South University, Changsha, China
2. School of Automation, Central South University, Changsha, China
3. University of Oulu, Oulu, Finland
4. National University of Defense Technology, Changsha, China
Funder
National Natural Science Foundation of China
Hunan Provincial Natural Science Foundation
Science and Technology Innovation Program of Hunan Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/9424/10492621/10413191.pdf?arnumber=10413191
Reference38 articles.
1. Automated Visual Defect Detection for Flat Steel Surface: A Survey
2. Scale-selective and noise-robust extended local binary pattern for texture classification
3. A noise robust method based on completed local binary patterns for hot-rolled steel strip surface defects
4. PGA-Net: Pyramid Feature Fusion and Global Context Attention Network for Automated Surface Defect Detection
5. MSC-DNet: An efficient detector with multi-scale context for defect detection on strip steel surface
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3. SCFNet: Lightweight Steel Defect Detection Network Based on Spatial Channel Reorganization and Weighted Jump Fusion;Processes;2024-05-02
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