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Wavelet Transform and Machine Learning-Based Biometric Authentication Using EEG Evoked by Invisible Visual Stimuli
https://repository.lib.tottori-u.ac.jp/records/7045
https://repository.lib.tottori-u.ac.jp/records/7045ebaaa025-76d0-44ca-b1f0-7d0feeb8c060
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
TENCON2020_Miyakle.pdf (1.5 MB)
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| Item type | 会議発表論文 / Conference Paper(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2020-11-20 | |||||
| タイトル | ||||||
| タイトル | Wavelet Transform and Machine Learning-Based Biometric Authentication Using EEG Evoked by Invisible Visual Stimuli | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Biometric authentication | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Invisible stimulation Machine Learning | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Electroencephalogram (EEG) | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Wavelet Transform | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Biometric authentication | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Invisible stimulation Machine Learning | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Electroencephalogram (EEG) | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Wavelet Transform | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||
| 資源タイプ | conference paper | |||||
| 著者 |
中西, 功
× 中西, 功× Miyake, Takahiro× Kinjo, Nozomu |
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| 著者所属（英） | ||||||
| 言語 | en | |||||
| 値 | Graduate School of Sustainability Sciences Tottori University | |||||
| 著者所属（英） | ||||||
| 言語 | en | |||||
| 値 | Graduate School of Sustainability Sciences Tottori University | |||||
| 著者所属（英） | ||||||
| 言語 | en | |||||
| 値 | Faculty of Engineering, Tottori University | |||||
| 抄録 | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | In this study, we propose the authentication of individuals using electroencephalograms (EEGs) evoked by the application of invisible visual stimuli. In our previous study, we introduced a wavelet transform, which is a time-frequency analysis method, and applied it to extract features, including time information, to enable more accurate discrimination between individuals. An equal error rate (EER) of 9.4 % was achieved using Euclidean distance matching. In this paper, we introduce a machine learning-based approach in order to further improve the verification performance. An EER of 8.1 % is achieved by the proposed method after training the constituent neural networks using ensemble learning with 30 networks. | |||||
| 書誌情報 |
Proceedings of the 2020 IEEE Region 10 Conference (TENCON2020) en : Proceedings of the 2020 IEEE Region 10 Conference (TENCON2020) 発行日 2020-11 |
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| 権利 | ||||||
| 権利情報 | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collec | |||||
| 情報源 | ||||||
| 関連名称 | T. Miyake, N. Kinjo, I.Nakanishi. Wavelet Transform and Machine Learning-Based Biometric Authentication Using EEG Evoked by Invisible Visual Stimuli. Proceedings of the 2020 IEEE Region 10 Conference (TENCON2020). 2020. | |||||
| 著者版フラグ | ||||||
| 出版タイプ | AM | |||||
| 出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||
