High-accuracy and lightweight weld surface defect detector based on graph convolution decoupling head
Guanqiang Wang,
Mingsong Chen,
Yongcheng Lin
et al.
Abstract:The essence of the difficulties for weld surface detection is that there is a lot of interference information during detection. This study aims to enhance the detection accuracy while keeping great deployment capabilities of a detection model for weld surface defects. To achieve this goal, an improved Yolo-GCH model is proposed based on the stable and fast Yolo-v5. The improvements primarily involve introducing a graph convolution network combined with a self-attention mechanism in the head part (i.e., GCH). T… Show more
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