Lisang Liu1, Chengyang Ke1,*, He Lin2
CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2443-2461, 2023, DOI:10.32604/cmc.2023.042582
Abstract Aiming at the problems of inaccurate edge segmentation, the hole phenomenon of segmenting large-scale targets, and the slow segmentation speed of printed circuit boards (PCB) in the image segmentation process, a PCB image segmentation model Mobile-Deep based on DeepLabv3+ semantic segmentation framework is proposed. Firstly, the DeepLabv3+ feature extraction network is replaced by the lightweight model MobileNetv2, which effectively reduces the number of model parameters; secondly, for the problem of positive and negative sample imbalance, a new loss function is composed of Focal Loss combined with Dice Loss to solve the category imbalance and improve the model discriminative ability; in… More >
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