Classification Algorithm of Logistics Packaging Based on Multi-scale Convolutional Neural Network

The rapid development of economy and society has led to the rapid increase of the output of logistics outer packaging garbage. How to realize the classification and recycling of logistics packaging garbage by intelligent methods has become a key factor for human beings to achieve sustainable development. To solve this problem, this paper proposes an image recognition model of logistics packaging, which is a convolution neural network model based on multi-scale, and adds channel and spatial attention mechanism. The model uses multi-scale convolution to extract richer image features. The attention mechanism is used to adaptively adjust the parts that need to be focused on, and the feature extraction ability of the model is enhanced. Compared with the traditional manual sorting method, this paper uses the deep learning technology to intelligently and automatically classify the logistics outer packaging. The experimental results show that the classification accuracy of data sets can reach 96% by using the method of deep learning, which is very helpful to improve the classification efficiency of logistics outer packaging.