Emotion recognition from spatiotemporal EEG representations with hybrid convolutional recurrent neural networks via wearable multi-channel headset.

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Title: Emotion recognition from spatiotemporal EEG representations with hybrid convolutional recurrent neural networks via wearable multi-channel headset.
Authors: Chen, Jingxia1,2, chenjx_sust@foxmail.com, Jiang, Dongmei1, Zhang, Yanning1, Zhang, Pengwei2
Source: Computer Communications; Mar2020, Vol. 154, p58-65, 8p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 142392698
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Emotion recognition from spatiotemporal EEG representations with hybrid convolutional recurrent neural networks via wearable multi-channel headset.
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  Data: <searchLink fieldCode="AU" term="%22Chen%2C+Jingxia%22">Chen, Jingxia</searchLink><relatesTo>1,2</relatesTo>, <i>chenjx_sust@foxmail.com</i><br /><searchLink fieldCode="AU" term="%22Jiang%2C+Dongmei%22">Jiang, Dongmei</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Zhang%2C+Yanning%22">Zhang, Yanning</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Zhang%2C+Pengwei%22">Zhang, Pengwei</searchLink><relatesTo>2</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Computer+Communications%22">Computer Communications</searchLink>; Mar2020, Vol. 154, p58-65, 8p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=142392698
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.comcom.2020.02.051
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      – Code: eng
        Text: English
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        PageCount: 8
        StartPage: 58
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      – TitleFull: Emotion recognition from spatiotemporal EEG representations with hybrid convolutional recurrent neural networks via wearable multi-channel headset.
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            NameFull: Chen, Jingxia
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            NameFull: Jiang, Dongmei
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            NameFull: Zhang, Yanning
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              Text: Mar2020
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              Y: 2020
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              Value: 154
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