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The lightweight network MobileNetV2 is more suitable for lip print recognition, but the recognition accuracy of this model needs to be improved compared with the existing machine learning recognition algorithms. The attention mechanism module and the grouped multi-scale feature fusion module are designed to not only increase the model\u2019s ability to finely represent texture features, extract features, and adapt to different input scales but also to further compress the number of parameters in the network model. The ablation experimental results show that the improved recognition model achieves 98.56% recognition accuracy. 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