Analysis of Commodity image recognition based on deep learning

Abstract

Deep learning has developed rapidly in recent years, especially in the field of image recognition. In this paper, the commodity recognition based on object detection method using deep convolutional neutral networks is investigated. Firstly, the commodity image dataset in real-world retail product checkout situations is constructed. Then, the image data is trained via object detection deep networks. Finally, three representative deep learning methods involving YOLOv3, Faster R-CNN and RetinaNet are analyzed in detail. The experimental results show the effectiveness of our proposed approach.