Next, we provide the details of public datasets which could be used for deep learning. More specifically, this paper reviews the key challenges of deep learning for retail product recognition and discusses potential techniques that can be helpful for the research of the topic. This article aims to present a comprehensive literature review of recent research on deep learning-based retail product recognition. In recent years, deep learning enjoys a flourishing evolution with tremendous achievements in image classification and object detection. It receives increasing consideration due to the great application prospect, such as automatic checkout, stock tracking, planogram compliance, and visually impaired assistance. Product recognition via images is a challenging task in the field of computer vision. The realization of automatic product recognition has great significance for both economic and social progress because it is more reliable than manual operation and time-saving. Taking time to identify expected products and waiting for the checkout in a retail store are common scenes we all encounter in our daily lives.
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