A CNN -based comparing network for the detection of steady-state visual evoked potential responses
文献类型:期刊论文
作者 | Xing, Jiezhen1,2,3; Qiu, Shuang1,2; Ma, Xuelin1,2,3; Wu, Chenyao1,2,3; Li, Jinpeng1,2,3; Wang, Shengpei1,2,3; He, Huiguang1,2,3,4 |
刊名 | NEUROCOMPUTING |
出版日期 | 2020-08-25 |
卷号 | 403页码:452-461 |
ISSN号 | 0925-2312 |
DOI | 10.1016/j.neucom.2020.03.048 |
通讯作者 | He, Huiguang(huiguang.he@ia.ac.cn) |
WOS关键词 | CANONICAL CORRELATION-ANALYSIS ; BRAIN ; INTERFACE ; REHABILITATION ; CLASSIFICATION ; RECOGNITION ; COMPONENTS ; SPEED |
资助项目 | National Natural Science Foundation of China[81701785] ; National Natural Science Foundation of China[61976209] ; CAS International Collaboration Key Project[173211KYSB20190024] ; Strategic Priority Research Program of CAS[XDB32040000] |
WOS研究方向 | Computer Science |
语种 | 英语 |
出版者 | ELSEVIER |
WOS记录号 | WOS:000541448000011 |
资助机构 | National Natural Science Foundation of China ; CAS International Collaboration Key Project ; Strategic Priority Research Program of CAS |
源URL | [http://ir.ia.ac.cn/handle/173211/39903] |
专题 | 类脑智能研究中心_神经计算及脑机交互 |
通讯作者 | He, Huiguang |
作者单位 | 1.Chinese Acad Sci, Res Ctr Brain Inspired Intelligence, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Xing, Jiezhen,Qiu, Shuang,Ma, Xuelin,et al. A CNN -based comparing network for the detection of steady-state visual evoked potential responses[J]. NEUROCOMPUTING,2020,403:452-461. |
APA | Xing, Jiezhen.,Qiu, Shuang.,Ma, Xuelin.,Wu, Chenyao.,Li, Jinpeng.,...&He, Huiguang.(2020).A CNN -based comparing network for the detection of steady-state visual evoked potential responses.NEUROCOMPUTING,403,452-461. |
MLA | Xing, Jiezhen,et al."A CNN -based comparing network for the detection of steady-state visual evoked potential responses".NEUROCOMPUTING 403(2020):452-461. |
入库方式: OAI收割
来源:自动化研究所
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