{"title":"基于深度学习的用户特征实时识别系统","authors":"Dennis Núñez","doi":"10.1109/INTERCON.2018.8526381","DOIUrl":null,"url":null,"abstract":"This paper describes an implementation of a novel real-time recognition system which is capable to identify important information from a single user such as gender, age, emotions and hand gestures. The key of this recognition system is the classification process. This is carried out by using several convolutional neural networks that were designed to achieve a high accuracy rate and acceptable response time making use of low computational resources. As a result, this recognition system could be useful in numerous applications like human-computer interaction, person identification, security control and others.","PeriodicalId":305576,"journal":{"name":"2018 IEEE XXV International Conference on Electronics, Electrical Engineering and Computing (INTERCON)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Real-Time Recognition System for User Characteristics Based on Deep Learning\",\"authors\":\"Dennis Núñez\",\"doi\":\"10.1109/INTERCON.2018.8526381\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes an implementation of a novel real-time recognition system which is capable to identify important information from a single user such as gender, age, emotions and hand gestures. The key of this recognition system is the classification process. This is carried out by using several convolutional neural networks that were designed to achieve a high accuracy rate and acceptable response time making use of low computational resources. As a result, this recognition system could be useful in numerous applications like human-computer interaction, person identification, security control and others.\",\"PeriodicalId\":305576,\"journal\":{\"name\":\"2018 IEEE XXV International Conference on Electronics, Electrical Engineering and Computing (INTERCON)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE XXV International Conference on Electronics, Electrical Engineering and Computing (INTERCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INTERCON.2018.8526381\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE XXV International Conference on Electronics, Electrical Engineering and Computing (INTERCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INTERCON.2018.8526381","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Real-Time Recognition System for User Characteristics Based on Deep Learning
This paper describes an implementation of a novel real-time recognition system which is capable to identify important information from a single user such as gender, age, emotions and hand gestures. The key of this recognition system is the classification process. This is carried out by using several convolutional neural networks that were designed to achieve a high accuracy rate and acceptable response time making use of low computational resources. As a result, this recognition system could be useful in numerous applications like human-computer interaction, person identification, security control and others.