S
Santanu Chaudhury
Researcher at Indian Institute of Technology, Jodhpur
Publications - 389
Citations - 4361
Santanu Chaudhury is an academic researcher from Indian Institute of Technology, Jodhpur. The author has contributed to research in topics: Ontology (information science) & Deep learning. The author has an hindex of 28, co-authored 380 publications receiving 3691 citations. Previous affiliations of Santanu Chaudhury include Central Electronics Engineering Research Institute & Indian Institute of Technology Delhi.
Papers
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Journal ArticleDOI
Feature combination for binary pattern classification
TL;DR: A novel binary multiple kernel learning-based classification architecture for applications including characters/primitives and symbols including such problems for fast and efficient performance is demonstrated.
Journal ArticleDOI
Tractography-Based Score for Learning Effective Connectivity From Multimodal Imaging Data Using Dynamic Bayesian Networks
TL;DR: A novel anatomically informed (AI) score that evaluates fitness of a given connectivity structure to both DTI and fMRI data simultaneously is proposed that is employed in structure learning of DBN given the data.
Proceedings ArticleDOI
An ontology-driven context aware framework for smart traffic monitoring
TL;DR: This paper discusses the key tasks of vision and probabilistic reasoning components that provide a feasible solution to identify the cause of traffic jam and shows effectiveness of real-time vehicle monitoring to assess congestion on road and offer user an assistive environment to operate.
Proceedings ArticleDOI
Link Prediction in Heterogeneous Social Networks
Sumit Negi,Santanu Chaudhury +1 more
TL;DR: The problem of link prediction in heterogeneous networks as a multi-task, metric learning (MTML) problem is posed and the MT-SPML method is extended to account for task correlations, robustness to non-informative features and non-stationary degree distribution across networks.
Journal ArticleDOI
Video analytics revisited
TL;DR: In this study, the authors discuss various issues and problems in video analytics, proposed solutions and present some of the important current applications of video analytics.