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What is Neural Networks for Metal Defect Detection about?

This paper investigates various deep learning-based neural networks for real-time metal surface defect detection, comparing the performance of Faster R-CNN, YOLO, and SSD using the NEU-DET dataset. The study finds that while Faster R-CNN offers high accuracy, it lacks the speed required for real-time applications, whereas YOLOv7 provides a balance of efficiency and accuracy, making it suitable for defect detection tasks. Future work aims to enhance YOLOv7

Author

Md Afeef

Language

EN