Himanshu Agrawal

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We study networks constructed from gene expression data obtained from many types of cancers. The networks are constructed by connecting vertices that belong to each others' list of K nearest neighbors, with K being an a priori selected non-negative integer. We introduce an order parameter for characterizing the homogeneity of the networks. On minimizing the(More)
Face is a complex multidimensional visual model and developing a computational model for face recognition is difficult. The paper presents a methodology for face recognition based on information theory approach of coding and decoding the face image. Proposed methodology is connection of two stages – Feature extraction using principle component analysis and(More)
This paper addresses the problem of retrieval from graph databases. Graph databases store graph structures instead of tables. Typically, graph databases are applicable in domains that require storage and retrieval of structural information. One of the main issues in graph databases is retrieval of member graphs based on structure matching. Structure(More)
In this paper, we propose a simple video summarization system based on removal of similar frames and the maintenance of unique frames. It tries to capture the temporal content of the frame and to output the video with a length specified by the user. It aims at eliminating similar frames by a process of clustering where similar frames are clustered into one(More)
We study counter expressed gene networks constructed from gene-expression data obtained from many types of cancers. The networks are synthesized by connecting vertices belonging to each others' list of K-farthest-neighbors, with K being an a priori selected non-negative integer. In the range of K corresponding to minimum homogeneity, the degree distribution(More)
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