增强基于脑电图的情绪识别的混合顺序前向信道选择方法

IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Experimental & Theoretical Artificial Intelligence Pub Date : 2024-01-11 DOI:10.1080/0952813x.2023.2301367
Shyam Marjit, Parag Jyoti Das, Upasana Talukdar, Shyamanta M Hazarika
{"title":"增强基于脑电图的情绪识别的混合顺序前向信道选择方法","authors":"Shyam Marjit, Parag Jyoti Das, Upasana Talukdar, Shyamanta M Hazarika","doi":"10.1080/0952813x.2023.2301367","DOIUrl":null,"url":null,"abstract":"In recent times, EEG-based emotion recognition has gained significant attention in affective computing. One of the major challenges in designing an efficient EEG-based emotion-recognition framework...","PeriodicalId":15677,"journal":{"name":"Journal of Experimental & Theoretical Artificial Intelligence","volume":"7 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A hybrid sequential forward channel selection method for enhancing EEG-Based emotion recognition\",\"authors\":\"Shyam Marjit, Parag Jyoti Das, Upasana Talukdar, Shyamanta M Hazarika\",\"doi\":\"10.1080/0952813x.2023.2301367\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent times, EEG-based emotion recognition has gained significant attention in affective computing. One of the major challenges in designing an efficient EEG-based emotion-recognition framework...\",\"PeriodicalId\":15677,\"journal\":{\"name\":\"Journal of Experimental & Theoretical Artificial Intelligence\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2024-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Experimental & Theoretical Artificial Intelligence\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1080/0952813x.2023.2301367\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Experimental & Theoretical Artificial Intelligence","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1080/0952813x.2023.2301367","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

摘要

近来,基于脑电图的情感识别在情感计算领域备受关注。设计基于脑电图的高效情感识别框架的主要挑战之一是...
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 hybrid sequential forward channel selection method for enhancing EEG-Based emotion recognition
In recent times, EEG-based emotion recognition has gained significant attention in affective computing. One of the major challenges in designing an efficient EEG-based emotion-recognition framework...
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
CiteScore
6.10
自引率
4.50%
发文量
89
审稿时长
>12 weeks
期刊介绍: Journal of Experimental & Theoretical Artificial Intelligence (JETAI) is a world leading journal dedicated to publishing high quality, rigorously reviewed, original papers in artificial intelligence (AI) research. The journal features work in all subfields of AI research and accepts both theoretical and applied research. Topics covered include, but are not limited to, the following: • cognitive science • games • learning • knowledge representation • memory and neural system modelling • perception • problem-solving
期刊最新文献
Occlusive target recognition method of sorting robot based on anchor-free detection network An effectual underwater image enhancement framework using adaptive trans-resunet ++ with attention mechanism An experimental study of sentiment classification using deep-based models with various word embedding techniques Sign language video to text conversion via optimised LSTM with improved motion estimation An efficient safest route prediction-based route discovery mechanism for drivers using improved golden tortoise beetle optimizer
×
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