☆ 4.6 Article

Improved YOLOV4-CSP Algorithm for Detection of Bamboo Surface Sliver Defects With Extreme Aspect Ratio

IEEE ACCESS (2022)

A steel surface defect inspection approach towards smart industrial monitoring

Ruiyang Hao et al.

Summary: The study introduces a steel surface defect inspection model that extracts complex features from multi-shape steel surface defects using a deformable convolution enhanced backbone network. A feature fusion network with balanced feature pyramid generates high-quality multi-resolution feature maps for the inspection of multi-size defects, and a detector network achieves the localization and classification of steel surface defects. The proposed model achieves high efficiency in inference with a mAP of 0.805, 0.144 higher than baseline models, while maintaining a balance between inspection performance and inference efficiency.

JOURNAL OF INTELLIGENT MANUFACTURING (2021)

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Review Computer Science, Information Systems