Bridging low-level features and high-level semantics via fMRI brain imaging for video classification

doi:10.1145/1873951.1874016

Bridging low-level features and high-level semantics via fMRI brain imaging for video classification

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Authors:	Xintao Hu	Northwestern Polytechnical University, Xi'an, China
	Fan Deng	the University of Georgia, Athens, GA, USA
	Kaiming Li	Northwestern Polytechnical University, Xi'an, China
	Tuo Zhang	Northwestern Polytechnical University, Xi'an, China
	Hanbo Chen	Northwestern Polytechnical University, Xi'an, China
	Xi Jiang	Northwestern Polytechnical University, Xi'an, China
	Jinglei Lv	Northwestern Polytechnical University, Xi'an, China
	Dajiang Zhu	the University of Georgia, Athens, GA, USA
	Carlos Faraco	the University of Georgia, Athens, GA, USA
	Degang Zhang	Northwestern Polytechnical University, Xi'an, China
	Arsham Mesbah	the University of Georgia, Athens, GA, USA
	Junwei Han	Northwestern Polytechnical University, Xi'an, China
	Xiansheng Hua	Microsoft Research Asia, Beijing, China
	Li Xie	Zhejiang University, Zhejiang, China
	Stephen Miller	the University of Georgia, Athens, GA, USA
	Lei Guo	Northwestern Polytechnical University, Xi'an, China
	Tianming Liu	the University of Georgia, Athens, GA, USA

	2010 Article
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	· Proceeding
	MM '10 Proceedings of the international conference on Multimedia
	Pages 451-460 ACM New York, NY, USA ©2010 table of contents ISBN: 978-1-60558-933-6 doi>10.1145/1873951.1874016

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Tags: algorithms brain computer interface brain imaging design experimentation high-level features human factors human factors human information processing human vision low-level features semantics video

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