YOLOv7-WDD: An Efficient Bi-directional Feature Aggregation Method for Workpiece Defect Detection
Author:
Affiliation:
1. Lanzhou University of Technology,School of Computer and Communication Technology,Lanzhou,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10593799/10594004/10594267.pdf?arnumber=10594267
Reference16 articles.
1. Deep Learning for Automatic Vision-Based Recognition of Industrial Surface Defects: A Survey
2. Approaches for improvement of the X-ray image defect detection of automobile casting aluminum parts based on deep learning
3. AFF-Net: A Strip Steel Surface Defect Detection Network via Adaptive Focusing Features
4. Steel Surface Defect Detection Using Improved Deep Learning Algorithm: ECA-SimSPPF-SIoU-Yolov5
5. Steel Surface Defect Detection Method Based on Improved YOLOX
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