With the growing e-commerce market and the increasing diversity of commodities, it brings great challenges for platforms and merchants to quickly and accurately annotate commodities. Multi-task commodity image classification technology combining attribute prediction, category classification and other tasks comes into being. This paper mainly studies the classification of commodity information based on convolutional neural network (CNN). Firstly, this paper analyzes the principle of CNN as the research basis, and uses the improved VGG16 CNN to build the structure of clothing product classification algorithm. Through the experimental results, we can know that the classification algorithm constructed in this paper can improve the goal of clothing image classification accuracy.

James Yong Liao. Product Information Classification based on Convolutional Neural Network. International Journal of Neural Network (2022), Vol. 3, Issue 3: 65-71. https://doi.org/10.38007/NN.2022.030308.

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