JOURNAL ARTICLE

Research on Classification of Cross-Border E-Commerce Products Based on Image Recognition and Deep Learning

Chen Rui

Year: 2020 Journal:   IEEE Access Vol: 9 Pages: 108083-108090   Publisher: Institute of Electrical and Electronics Engineers

Abstract

Cross-border e-commerce is a concrete manifestation of “Internet + foreign trade”, which is conducive to improving the people’s material living standards and quality, and is also the key to promoting my country’s industrial transformation and upgrading. E-commerce platform is the carrier of cross-border e-commerce, and product classification plays a very important role in the e-commerce platform. Aiming at the shortcomings of existing product classification, this paper develops a new classification technology. First, obtain the relevant parameters of the product image through image recognition technology. Secondly, a cross-border e-commerce product classification model is constructed through deep learning technology, and Gray and RGB features of convolution and recursive networks are combined when training the classifier to enhance feature expression. Finally, the applicability and efficiency of related models are verified through performance and functional tests. This technology can effectively improve the rationality of the functional design of the e-commerce platform, thereby improving the efficiency of cross-border commerce business.

Keywords:
Computer science Classifier (UML) RGB color model Deep learning Product (mathematics) Artificial intelligence Contextual image classification The Internet Key (lock) Machine learning Image (mathematics) World Wide Web Computer security Mathematics

Metrics

18
Cited By
2.59
FWCI (Field Weighted Citation Impact)
26
Refs
0.90
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

E-commerce and Technology Innovations
Social Sciences →  Business, Management and Accounting →  Business and International Management
Advanced Computing and Algorithms
Social Sciences →  Social Sciences →  Urban Studies
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