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The task of visual tracking is to deal with dynamic image streams that change over time. For color object tracking, although a color object is a 3-order tensor in essence, little attention has been focused on this attribute. In this paper, we propose a novel Incremental Multiple Principal Component Analysis (IMPCA) method for online learning dynamic tensor streams. When newly added tensor set arrives,...
We have developed a time-shift map of the brain, which shows/ visualizes signal such as EEG and MEG etc. is transmitted/ propagated at each brain part where in each frequency band action potential information of time-to-time is transmitted to and processed at exact remote portion. Assuming the memory is composed of loop neural circuit in the cerebral cortex, we have also shown a feasibility of self...
Image category recognition is important to access visual information on the level of objects and scene types. This paper combines different feature representations of images and learn a compact subspace of different features for the automatic recognition of object and scene classes. Compact visual-words and low-level-features object class subspaces are automatically learned from a set of training...
Traditional reinforcement learning always emphasizes the independent learning of a single agent. In Multi-Agent System (MAS), considering the relationship between independent learning and group learning, this paper presents a hybrid algorithm based on average reward reinforcement learning. In learning process of the modified algorithm, it still pays attention to the independent learning. In order...
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