Steel surface defect detection algorithm using deep learning

Fei Ren; JiaJie Fei; Mary Jane Samonte; HongSheng Li; Bonifacio T. Doma Jr.

doi:10.1117/12.3013355

29 November 2023 Steel surface defect detection algorithm using deep learning

Fei Ren, JiaJie Fei, Mary Jane Samonte, HongSheng Li, Bonifacio T. Doma Jr.

Proceedings Volume 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023); 129370P (2023) https://doi.org/10.1117/12.3013355
Event: International Conference on Internet of Things and Machine Learning (IoTML 2023), 2023, Singapore, Singapore

Abstract

Steel surface defect detection has always been a research hotspot in smart factories. Aiming at the problem of insufficient recall and speed of the Yolov5 algorithm in detecting steel surface defects, the steel surface detection effect was improved by new deep learning algorithm based on Yolov5 algorithm combined with different attention mechanism algorithms. SE, ECA, and C3SE attention mechanism modules were respectively added to Yolov5's backbone in this paper, which improved the weight of important feature information, reduced the attention to other information, and improved detection recall. The experimental results indicated that the improved Yolov5 deep learning model can greatly improve recall. Compared with YOLOv5, the recall of ECA-YOLOv5 was slightly improved; the recall of SE-YOLOv5 was obvious improved, and the Inference time was reduced by 0.1ms; The recall and mAP@.5 of C3SE-YOLOv5 were significantly improved. The total parameter count of the network decreased by 13.03%, at the same time the pt file size of the network decreased by 12.72%. The improved network significantly improved the performance of the steel surface defect detection algorithm.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Fei Ren, JiaJie Fei, Mary Jane Samonte, HongSheng Li, and Bonifacio T. Doma Jr. "Steel surface defect detection algorithm using deep learning", Proc. SPIE 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023), 129370P (29 November 2023); https://doi.org/10.1117/12.3013355

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