计算机与现代化Issue(4)：60-65,6.DOI:10.3969/j.issn.1006-2475.2024.04.011
基于深度学习的超市果蔬检索方法
Supermarket Fruit and Vegetable Retrieval Method Based on Deep Learning
摘要
Abstract
In view of the problems that the current settlement method of supermarket fruits and vegetables cannot add new catego-ries and low accuracy of small sample recognition,this paper proposes a supermarket fruits and vegetables retrieval method based on deep learning.The method obtains fruit and vegetable subjects through YOLOv4 to remove redundant background infor-mation,and extracts corresponding deep semantic features of fruit and vegetable subjects through MobileNetV3.Finally,cat-egory judgment is completed according to metric learning technology.This paper conducts experiments in accordance with the ac-tual operation conditions of supermarkets and concludes that the method could accurately identify different fruit and vegetable cat-egories under the condition of small samples.When the number of samples for each category is 15,the average recognition rate is about 94%,the time cost is 0.93s,and the new categories could be updated in real time.This method greatly reduces the huge la-bor and time cost in the actual operation of traditional supermarkets,and provides a solution for the realization of intelligence and automation in the fruit and vegetable retail industry.关键词
图像检索/果蔬识别/类别增加/小样本识别Key words
image retrieval/fruit and vegetable recognition/category increase/small sample recognition分类
信息技术与安全科学引用本文复制引用
郭泽昕,钟国韵,何剑锋,张军..基于深度学习的超市果蔬检索方法[J].计算机与现代化,2024,(4):60-65,6.基金项目
国家自然科学基金资助项目(62162002) （62162002）
江西省主要学科学术和技术带头人培养计划—领军人才项目(20225BCJ22004) （20225BCJ22004）
