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Drift is the most difficult issue in object visual tracking based on framework of “tracking-by-detection”. Due to the self-taught learning, the mis-aligned samples are potentially to be incorporated in learning and degrade the discrimination of the tracker. This paper proposes a new tracking approach that resolves this problem by three multi-level collaborative components: a high-level global appearance...
Identifying the subject's simple judging states from fMRI data is the basis of studying complex logical relationship and has great theoretical significance. In this paper, we study judging states from fMRI data in terms of logical recognition classifications. We found that the ROI (Regions of Interest) regions played an important role in visual recognition task and identified what ROI regions were...
To investigate the neural activity corresponding to different cognitive states, it is of great importance to localize the cortical areas that are associated with task-related modulation. In this paper, we propose a novel discriminant pattern source localization (DPSL) method to analyze MEG data. Unlike most traditional source localization methods that aim to find “dominant” sources, DPSL is developed...
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