Deep Learning for Retail Product Recognition: Challenges and Techniques
Joint Authors
Wei, Yuchen
Tran, Son
Xu, Shuxiang
Kang, Byeong
Springer, Matthew
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-23, 23 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-12
Country of Publication
Egypt
No. of Pages
23
Main Subjects
Abstract EN
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.
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.
Product recognition via images is a challenging task in the field of computer vision.
It receives increasing consideration due to the great application prospect, such as automatic checkout, stock tracking, planogram compliance, and visually impaired assistance.
In recent years, deep learning enjoys a flourishing evolution with tremendous achievements in image classification and object detection.
This article aims to present a comprehensive literature review of recent research on deep learning-based retail product recognition.
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.
Next, we provide the details of public datasets which could be used for deep learning.
Finally, we conclude the current progress and point new perspectives to the research of related fields.
American Psychological Association (APA)
Wei, Yuchen& Tran, Son& Xu, Shuxiang& Kang, Byeong& Springer, Matthew. 2020. Deep Learning for Retail Product Recognition: Challenges and Techniques. Computational Intelligence and Neuroscience،Vol. 2020, no. 2020, pp.1-23.
https://search.emarefa.net/detail/BIM-1138934
Modern Language Association (MLA)
Wei, Yuchen…[et al.]. Deep Learning for Retail Product Recognition: Challenges and Techniques. Computational Intelligence and Neuroscience No. 2020 (2020), pp.1-23.
https://search.emarefa.net/detail/BIM-1138934
American Medical Association (AMA)
Wei, Yuchen& Tran, Son& Xu, Shuxiang& Kang, Byeong& Springer, Matthew. Deep Learning for Retail Product Recognition: Challenges and Techniques. Computational Intelligence and Neuroscience. 2020. Vol. 2020, no. 2020, pp.1-23.
https://search.emarefa.net/detail/BIM-1138934
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1138934