PCB surface component detection algorithm based on CSTDNet
PCB surface components are characterized by dense distribution,small size,and similar appearances,making it challenging to accurately detect and identify issues.Therefore,this paper proposes a Cross-Scale Task Dynamic Network(CSTDNet)PCB surface component detection algorithm based on VFNet.Building upon VFNet,an algorithm named CSTDNet(Cross-Scale Task Dynamic Network)is proposed for the detection of PCB surface components.This algorithm incorporates a cross-scale interactive feature module into the fusion network to enhance the description capability of small components.Furthermore,a task alignment learning mechanism is integrated into the detection head network to optimize spatial consistency between classification and regression tasks.Additionally,a Gaussian dynamic soft label allocation strategy is introduced in the process of positive and negative sample selection to better compensate for the number of positive samples of small components.Experimental results show that the new detection algorithm improves the FPS,mAP,and mAP_s by 10.7%,11.8%and 7.6%,respectively,effectively enhancing the detection performance of small components in dense scenes.
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