Paper Abstract and Keywords |
Presentation |
2017-05-26 14:15
Frequency Filter Networks on EEG Data for Emotion Analysis Miku Yanagimoto, Chika Sugimoto, Tomoharu Nagao (YNU) NC2017-4 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In EEG-based emotion recognition (EEG-ER), enhancing feature extractors is often difficult.
In such cases, the use of deep neural networks which are capable of classification and recognition by the input of raw data is desirable.
Therefore, effective components and models of neural networks for EEG-based recognition must be proposed.
This paper proposes a discrete Fourier transform (DFT) layer, inverse DFT (IDFT) layer, and other components to compose a frequency filter module.
This module was proposed for embedding a bandpass filter suitable for EEG data and the targets.
The proposed models were compared with their counterparts and state-of-the-art models, and evaluated according to their accuracies for emotion recognition.
The results showed that the frequency filter module is effective in preprocessing or interpreting some features in EEG with a characteristic in frequency domain. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
neural networks / deep learning / Fourier transform / EEG / emotions / / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 64, NC2017-4, pp. 19-24, May 2017. |
Paper # |
NC2017-4 |
Date of Issue |
2017-05-19 (NC) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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NC2017-4 |
Conference Information |
Committee |
MBE NC |
Conference Date |
2017-05-26 - 2017-05-26 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Toyama Prefectural Univ. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
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Paper Information |
Registration To |
NC |
Conference Code |
2017-05-MBE-NC |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Frequency Filter Networks on EEG Data for Emotion Analysis |
Sub Title (in English) |
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Keyword(1) |
neural networks |
Keyword(2) |
deep learning |
Keyword(3) |
Fourier transform |
Keyword(4) |
EEG |
Keyword(5) |
emotions |
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1st Author's Name |
Miku Yanagimoto |
1st Author's Affiliation |
Yokohama National University (YNU) |
2nd Author's Name |
Chika Sugimoto |
2nd Author's Affiliation |
Yokohama National University (YNU) |
3rd Author's Name |
Tomoharu Nagao |
3rd Author's Affiliation |
Yokohama National University (YNU) |
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Speaker |
Author-1 |
Date Time |
2017-05-26 14:15:00 |
Presentation Time |
25 minutes |
Registration for |
NC |
Paper # |
NC2017-4 |
Volume (vol) |
vol.117 |
Number (no) |
no.64 |
Page |
pp.19-24 |
#Pages |
6 |
Date of Issue |
2017-05-19 (NC) |
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