Hailong Wang*, Junchao Shi
CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1109-1128, 2025, DOI:10.32604/cmc.2024.057706
- 03 January 2025
Abstract A two-stage algorithm based on deep learning for the detection and recognition of can bottom spray codes and numbers is proposed to address the problems of small character areas and fast production line speeds in can bottom spray code number recognition. In the coding number detection stage, Differentiable Binarization Network is used as the backbone network, combined with the Attention and Dilation Convolutions Path Aggregation Network feature fusion structure to enhance the model detection effect. In terms of text recognition, using the Scene Visual Text Recognition coding number recognition network for end-to-end training can alleviate… More >
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