A Deep Learning Facial Expression Recognition based Scoring System for Restaurants

W. Chang, Miriam Schmelzer, Florian Kopp, Chia-Hao Hsu, Jian-Ping Su, Liang-Bi Chen, Ming-Che Chen
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引用次数: 15

Abstract

Recently, the popularity of automated and unmanned restaurants has increased. Due to the absence of staff, there is no direct perception of the customers' impressions in order to find out what their experiences with the restaurant concept are like. For this purpose, this paper presents a rating system based on facial expression recognition with pre-trained convolutional neural network (CNN) models. It is composed of an Android mobile application, a web server, and a pre-trained AI-server. Both the food and the environment are supposed to be rated. Currently, three expressions (satisfied, neutral and disappointed) are provided by the scoring system.
基于深度学习面部表情识别的餐馆评分系统
最近,自动化和无人餐厅越来越受欢迎。由于没有工作人员,无法直接感知顾客的印象,无法了解他们对餐厅概念的体验。为此,本文提出了一种基于预训练卷积神经网络(CNN)模型的面部表情识别评分系统。它由Android移动应用程序、web服务器和预训练的ai服务器组成。食物和环境都应该被评级。目前,评分系统提供了三种表达(满意、一般和失望)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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