基于深度学习的用户特征实时识别系统

Dennis Núñez
{"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}
引用次数: 1

摘要

本文描述了一种新型实时识别系统的实现,该系统能够识别来自单个用户的重要信息,如性别、年龄、情绪和手势。该识别系统的关键是分类过程。这是通过使用几个卷积神经网络来实现的,这些神经网络旨在利用低计算资源实现高准确率和可接受的响应时间。因此,这种识别系统可以在人机交互、人员识别、安全控制等众多应用中发挥作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Water Level Monitoring System Based on LoPy4 Microcontroller with LoRa technology Mobile Technology Model to Collection Information of Self-Assisted Clinical History Design and Implementation of a Graphical User Interface for a Radar System Trajectory Tracking Control of a Differential Wheeled Mobile Robot: a Polar Coordinates Control and LQR Comparison JOHSAN – A multisensorial system to support the teaching-stimulation processes with children suffering from brain paralysis
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1