实验持续时间和超时空分析对脑电图分类方法的影响。

Simone Palazzo;Concetto Spampinato;Isaak Kavasidis;Daniela Giordano;Joseph Schmidt;Mubarak Shah
{"title":"实验持续时间和超时空分析对脑电图分类方法的影响。","authors":"Simone Palazzo;Concetto Spampinato;Isaak Kavasidis;Daniela Giordano;Joseph Schmidt;Mubarak Shah","doi":"10.1109/TPAMI.2024.3426296","DOIUrl":null,"url":null,"abstract":"Bharadwaj et al. (2023) present a comments paper evaluating the classification accuracy of several state-of-the-art methods using EEG data averaged over random class samples. According to the results, some of the methods achieve above-chance accuracy, while the method proposed in (Palazzo et al. 2020), that is the target of their analysis, does not. In this rebuttal, we address these claims and explain why they are not grounded in the cognitive neuroscience literature, and why the evaluation procedure is ineffective and unfair.","PeriodicalId":94034,"journal":{"name":"IEEE transactions on pattern analysis and machine intelligence","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Rebuttal to “Comments on ‘Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features’ ”\",\"authors\":\"Simone Palazzo;Concetto Spampinato;Isaak Kavasidis;Daniela Giordano;Joseph Schmidt;Mubarak Shah\",\"doi\":\"10.1109/TPAMI.2024.3426296\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Bharadwaj et al. (2023) present a comments paper evaluating the classification accuracy of several state-of-the-art methods using EEG data averaged over random class samples. According to the results, some of the methods achieve above-chance accuracy, while the method proposed in (Palazzo et al. 2020), that is the target of their analysis, does not. In this rebuttal, we address these claims and explain why they are not grounded in the cognitive neuroscience literature, and why the evaluation procedure is ineffective and unfair.\",\"PeriodicalId\":94034,\"journal\":{\"name\":\"IEEE transactions on pattern analysis and machine intelligence\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE transactions on pattern analysis and machine intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10592658/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE transactions on pattern analysis and machine intelligence","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10592658/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

Bharadwaj 等人[1]发表了一篇评论文章,利用随机类样本的平均脑电图数据评估了几种最先进方法的分类准确性。结果显示,其中一些方法达到了高于概率的准确度,而他们分析的目标--[2] 中提出的方法却没有达到。在这篇反驳文章中,我们将针对这些说法,解释为什么它们在认知神经科学文献中没有依据,以及为什么评估程序是无效和不公平的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rebuttal to “Comments on ‘Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features’ ”
Bharadwaj et al. (2023) present a comments paper evaluating the classification accuracy of several state-of-the-art methods using EEG data averaged over random class samples. According to the results, some of the methods achieve above-chance accuracy, while the method proposed in (Palazzo et al. 2020), that is the target of their analysis, does not. In this rebuttal, we address these claims and explain why they are not grounded in the cognitive neuroscience literature, and why the evaluation procedure is ineffective and unfair.
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
×
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