曾敏 吴圣健 李坊 陈直

摘要：近年来，基于深度学习模型的图像识别技术已成为智能零售柜的主要解决方案。设计了一种新的基于双神经网络模型的智能零售柜系统。该系统与单模型设计比较，除检测召回率和分类准确度有显著提升外，还大大降低了因增加新品种而导致的模型再训练时间。首先，利用Faster RCNN模型完成商品大类（按包装分类）的分类检测任务，以提高检测召回率;其次，利用ResNet50模型完成商品小类（按品种分类）的分类任务，以提高分类准确度。与此同时，还在最难分品种集上进行了多种数据增强消融实验研究，以改进该难分品种集所属大类数据集的分类准确度。

关键词：深度学习;图像检测;图像分类;智能零售柜;神经网络模型

中图分类号：TP181      文献标识码：A

文章编号：1009-3044（2021）26-0009-05

开放科学（资源服务）标识码（OSID）：

Design and Implementation of Intelligent Retail Cabinet Based on Double Neural Network Model

ZENGMin1，WU Sheng-jian2， LI Fang1， CHEN Zhi1

（1. Dept. of Communication and Information Engineering， Shanghai Technical institute of Electronics & information， Shanghai 201411， China;2. FinVolution Group， Shanghai 201203， China）

Abstract：In recent years， image recognition technology based on deep learning models has become the main solution for intelligent retail cabinets. A new intelligent retail cabinet system based on dual neural network model is introduced. Compared with the single model design， this system not only significantly enhances the detection recall rate and classification accuracy， but also greatly reduces the model retraining time caused by the addition of new varieties. First， the Faster RCNN model is used to complete the rough classification and detection task of commodity categories （classified by packaging） to improve the detection recall rate; secondly， the ResNet50 model is employed to complete the fine classification task of commodity categories （classified by variety） to improve classification accuracy degree. At the same time， some data augment ablation experiments were conducted on the most difficult-to-classification variety set of this project to refine the fine classification accuracy of the commodity categories （classified by variety） to which the difficult-to-classification variety set belongs.

Key words：deeplearning; image detection; image classification; intelligent retail cabinets; neural network model

近年来，无人零售作为一种便利的零售新业态，在我国许多城市得到了长足发展。根据前瞻产业研究院发布的《中国新零售行业商业模式创新与投资机会深度研究报告》预测，2022年无人零售用户可达2.45亿人，交易额将超1.8万亿元[1]。无人零售的快速增长，得益于多种技术的发展和融合，特别是移动支付的普及和人工智能、云计算等高新技术的应用落地[2]。

目前，我國无人值守零售柜有4种技术实现形式[3，5]，分别是①以“友宝公司”为代表的机械式自动售卖机。其发展较早，技术难度低，产品成熟，但制造成本较高，购物流程相对烦琐;②以“每日优鲜”为代表的RFID（Radio Frequency Identification）零售柜。……