Visual Emotion Recognition Using Deep Neural Networks

Alexander I. Iliev, Ameya Mote
{"title":"Visual Emotion Recognition Using Deep Neural Networks","authors":"Alexander I. Iliev, Ameya Mote","doi":"10.55630/dipp.2022.12.5","DOIUrl":null,"url":null,"abstract":"It has been proven historically how important feelings and expressions are. They form an important role in communications between individuals of different culture. In the present day, Globalization has led to exchange of vast number of ideas among people on Earth. This gives rise to a unique challenge of identifying what the person in front is speaking about and formulate opinions likewise. Failing to do that would often result in unfortunate consequences. This paper leads to make inroads in this field and provide a basis to other future researchers. We took images from a pre-existing video dataset and recognize the emotions behind it. Through a series of experiments, a final neural network model was created which gave an accuracy of 88%.","PeriodicalId":268414,"journal":{"name":"Digital Presentation and Preservation of Cultural and Scientific Heritage","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital Presentation and Preservation of Cultural and Scientific Heritage","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.55630/dipp.2022.12.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

It has been proven historically how important feelings and expressions are. They form an important role in communications between individuals of different culture. In the present day, Globalization has led to exchange of vast number of ideas among people on Earth. This gives rise to a unique challenge of identifying what the person in front is speaking about and formulate opinions likewise. Failing to do that would often result in unfortunate consequences. This paper leads to make inroads in this field and provide a basis to other future researchers. We took images from a pre-existing video dataset and recognize the emotions behind it. Through a series of experiments, a final neural network model was created which gave an accuracy of 88%.
基于深度神经网络的视觉情感识别
历史已经证明了情感和表达的重要性。它们在不同文化的个体之间的交流中起着重要的作用。在今天,全球化导致了地球上人们之间大量思想的交流。这就产生了一个独特的挑战,即确定前面的人在说什么,并提出同样的意见。如果做不到这一点,往往会导致不幸的后果。本文在这方面取得了一定的进展,并为今后的研究提供了一定的基础。我们从预先存在的视频数据集中提取图像,并识别其背后的情绪。通过一系列的实验,最终建立了一个神经网络模型,其准确率达到88%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信