The rapid iterative update of Internet technology has driven the development of the e-commerce industry. And the consumption concept of modern people has undergone great changes, from the initial real economy to the e-commerce economy. A large number of consumers are shopping online, and merchants need to package these products and then deliver them to consumers through logistics. In the process of commodity transportation, it is necessary to classify the logistics. At this time, it can be distinguished by the type of packaging. For example, by identifying the logistics packaging(LP) information, the commodities such as fragile products, easy-to-moisture products, etc. are separated from general commodities, so that the sorting personnel know Which needs to be handled with ease. In this regard, this paper designs an intelligent identification system for LP products, and introduces artificial neural network (ANN) and AlexNet-convolutional neural network (CNN) models. More intelligent. In order to verify the recognition effect of the improved AlexNet-CNN model, the recognition accuracy of LP image datasets under different network residuals was compared. The results show that the recognition accuracy is higher when the network residuals are larger and the datasets are more.

Fuqiang Tian. Intelligent Identification of Logistics Packaging Products Based on Neural Network. International Journal of Neural Network (2021), Vol. 2, Issue 2: 10-16. https://doi.org/10.38007/NN.2021.020202.

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