Jinpeng Yue

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Cognitive cycle is a basic procedure of mental activities in cognitive level. Human cognition consists of cascading cycles of recurring brain events. This paper presents a cognitive cycle for the mind model CAM (Consciousness and Memory). Each cognitive cycle perceives the current situation, through motivation phase with reference to ongoing goals, and then(More)
In multi-agent system, agents work together for solving complex tasks and reaching common goals. In this paper, we propose a cognitive model for multi-agent collaboration. Based on the cognitive model, an agent architecture will also be presented. This agent has BDI, awareness and policy driven mechanism concurrently. These approaches are integrated in one(More)
Cyborg intelligence will integrate the best of both machine and biological intelligences via brain-machine integration. To make this integration effective and coadaptive, multiagents should work collaboratively. Here, three levels of computational cognitive models for brain-machine collaboration are presented-awareness-based, motivational-based, and(More)
CCA is a powerful tool for analyzing paired multi-view data. However , when facing semi-paired multi-view data which widely exist in real-world problems, CCA usually performs poorly due to its requirement of data pairing between different views in nature. To cope with this problem, we propose a semi-paired variant of CCA named SemiPCCA based on the(More)
Clustering is fundamental in multimedia retrieval. For example, visual features of high dimensionality are extracted and clustered for image content analysis in image retrieval, scene classification and object retrieval applications. Existing clustering methods suffer from the curse of dimensionality when data are high dimensional and especially in large(More)
Cross-media is the outstanding characteristics of the age of big data with large scale and complicated processing task. This article presents 5 issues and briefly summarizes the research progress of cross-media knowledge discovery. Furthermore, we propose a framework for cross-media semantic understanding which contains discriminative modeling, generative(More)
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