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
More filters
Book ChapterDOI
Real-Time Vehicle Detection in Aerial Images Using Skip-Connected Convolution Network with Region Proposal Networks
TL;DR: This paper aims to provide a solution to the problem faced in real-time vehicle detection in aerial images and videos by using hyper maps generated by skip connected Convolutional network to generate object like proposals accurately.
Journal ArticleDOI
Novel view synthesis using a translating camera
TL;DR: A method for synthesis of views corresponding to translational motion of the camera, which can handle occlusions and changes in visibility in the synthesized views, and gives a characterisation of the viewpoints corresponding to which views can be synthesized.
Proceedings ArticleDOI
Most Discriminative Primitive Selection for Identity Determination Using Handwritten Devanagari Script
TL;DR: An approach for selecting best discriminative primitives for writer recognition is presented and a hybrid system by combining both writer recognition and handwriting recognition for improved accuracy is proposed.
Book ChapterDOI
Video scene interpretation using perceptual prominence and mise-en-scène features
Gaurav Harit,Santanu Chaudhury +1 more
TL;DR: In this article, the authors propose a perceptual prominence-based approach to the spatio-temporal domain of video, which is applied on blob tracks and makes use of a specified spatiotemporal coherence model.
Proceedings ArticleDOI
Best-fit mobile recharge pack recommendation
TL;DR: An adaptive recommendation model is discussed about which overcomes various deficiencies associated with existing solutions and recommends suitable recharge packs to subscribers based on their usage history and affordability.