Metal surface defect detection based on improved YOLOv5
Author:
Affiliation:
1. Beijing Institute of Graphic Communication,Department of Mechanical and Electrical Engineering,Beijing,China
2. Beijing Institute of Petrochemical Technology,Department of Information Engineering,Beijing,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10211117/10212989/10213124.pdf?arnumber=10213124
Reference10 articles.
1. Deep Learning for Generic Object Detection: A Survey
2. Application of improved YOLOV5 in plate defect detection
3. Steel Surface Defect Detection Based on Improved YOLOV5 Algorithm
4. Faster Metallic Surface Defect Detection Using Deep Learning with燙hannel燬huffling
5. Defect Detection for Metal Shaft Surfaces Based on an Improved YOLOv5 Algorithm and Transfer Learning
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1. Real-time defect detection systems for steel and wood inspection;2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE);2024-08-06
2. Automotive Parts Defect Detection Based on YOLOv7;Electronics;2024-05-08
3. Defect Detection Algorithm for Battery Cell Casings Based on Dual-Coordinate Attention and Small Object Loss Feedback;Processes;2024-03-18
4. ACD‐YOLO: Improved YOLOv5‐based method for steel surface defects detection;IET Image Processing;2023-11-11
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