Abstract: Cross-border retail is the key to Sino-Thai trade, but the traditional shopping experience using RFID tag recognition and
manual inquiry mode is not satisfactory. Therefore, the use of machine vision-based commodity identification method to build an
artificial intelligence retail e-commerce system of "Internet + cross-border trade" has important application value for promoting the
regional economic development of the China-Thailand "Belt and Road". Based on the research of image classification and recognition
technology and convolution neural network, this paper proposes an Inception-Thai neural network model on the basis of Inception-V3
framework parameter transfer learning for Thai commodity recognition, which can avoid over-fitting in a small number of samples. The
experimental results on seven types of Thai merchandise image datasets show that the model has a high ability to extract deep-seated
features of images, and the classification confidence of merchandise recognition can reach 83% to 98%, which achieves a high
accuracy.

Key words: cross-border retail, identification, deep learning, image classification