Soumyajit Ganguly

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In this paper, we consider the problem of learning representations for authors from bibliographic co-authorship networks. Existing methods for deep learning on graphs, such as DeepWalk, suffer from link sparsity problem as they focus on modeling the link information only. We hypothesize that capturing both the content and link information in a unified way(More)
We present Paper2vec, a novel neural network embedding based approach for creating scientific paper representations which make use of both textual and graph-based information. An academic citation network can be viewed as a graph where individual nodes contain rich textual information. With the current trend of open-access to most scientific literature, we(More)
Motion capturing and there by segmentation of the motion of any moving object from a sequence of continuous images or a video is not an exceptional task in computer vision area. Smart-phone camera application is an added integration for the development of such tasks and it also provides for a smooth testing. A new approach has been proposed for segmenting(More)
Image processing and computer vision are considered as one of the most promising as well as exciting domains of modern day engineering. Equipped with concepts of artificial intelligence and some very advanced algorithms and functions to deal with challenges of processing of images as well as to mimic gestures, these domains of engineering prove to be one of(More)
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