.png){kind=icon}
返回
Deep learning for EEG-based biometric recognition
.png){kind=icon}
PRE
AI
DOI：10.1016/j.neucom.2020.06.009.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The exploitation of brain signals for biometric recognition purposes has received significant attention from the scientific community in the last decade, with most of the efforts so far devoted to the quest for discriminative information within electroencephalography (EEG) recordings. Yet, currently-achievable recognition rates are still not comparable with those granted by more-commonly-used biometric characteristics, posing an issue for the practical deployment of EEG-based recognition in reallife applications. Within this regard, the present study investigates the effectiveness of deep learning techniques in extracting distinctive features from EEG signals. Both convolutional and recurrent neural networks, as well as their combinations, are employed as strategies to derive personal identifiers from the collected EEG data. In order to assess the robustness of the considered techniques, an extensive set of experimental tests is conducted under very challenging conditions, trying to determine whether it is feasible to identify subjects through their brain signals regardless the performed mental task, and comparing acquisitions collected at a temporal distance greater than one year. The obtained results suggest that the proposed networks are actually able to exploit the dynamic temporal behavior of EEG signals to achieve high-level accuracy for brain-based biometric recognition. (C) 2020 Elsevier B.V. All rights reserved.
Keyword:
Biometrics
Electroencephalography
Deep learning
Convolutional neural networks
Recurrent neural networks
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
机构
引用论文
分享收藏A novel deep learning approach for classification of EEG motor imagery signals一种新的用于脑电运动想象信号分类的深度学习方法
PREAI
分享收藏Brainprint: Assessing the uniqueness, collectability, and permanence of a novel method for ERP biometrics.png)
NEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
分享收藏CEREBRE: A Novel Method for Very High Accuracy Event-Related Potential Biometric Identification
PREAI
分享收藏EEG-based user identification system using 1D-convolutional long short-term memory neural networks基于脑电图的一维卷积长短期记忆神经网络用户识别系统
PREAI
分享收藏
查看更多内容