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This paper presents a highly scalable and adaptable co-learning framework on multimodal image retrieval and image annotation. The co-learning framework is based on the multiple instance learning theory. While this framework is a general framework that may be used in any specific domains, to evaluate this framework, we apply it to the Berkeley Drosophila ISH(More)
We consider the problem of discovering frequent item sets and association rules between items in a large database of transactional databases acquired under uncertainty. A probabilistic database considered here is one in which with each transaction associated is a probability, represents the confidence that the transaction will occur with given associated(More)
Temporal video segmentation using unsupervised clustering and semantic object tracking",A fuzzy k-nearest neighbor algorithm", IEEE Transactions on systems man, cybernetics. 12. Internal object-part structural information was not used in these tests, but detailed results are provided in [14]. The results above suggest that the framework presented here is(More)
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