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
Proceedings ArticleDOI
Despeckling CNN with Ensembles of Classical Outputs
TL;DR: A convolutional neural network is developed which learns to remove speckle from US images using the outputs of these classical approaches and is able to outperform the state-of-the-art despeckling approaches and produces the outputs even better than the ensembles for certain images.
Proceedings ArticleDOI
Intelligent Identification of Ornamental Devanagari Characters Inspired by Visual Fixations
TL;DR: It is found that the convolutional neural network performs better when trained with the assistance of fixation information compared to the network trained without eye fixations.
Proceedings ArticleDOI
Symmetry based 3D reconstruction of repeated cylinders
TL;DR: The combination of 360°-rotational symmetry and camera center is used to identify two orthogonal planes called axis plane and Orthogonal axis plane, which are the basis for the proposed reconstruction framework and virtual camera configuration.
Proceedings ArticleDOI
Curvature feature distribution based classification of Indian scripts from document images
TL;DR: A framework for classification of text document images based on their script and uses edge direction based features to capture the distribution of curvature and a recently proposed feature selection algorithm to obtain the most discriminating curvature features.
Proceedings ArticleDOI
Parameterized variety for multi-view multi-exposure image synthesis and high dynamic range stereo reconstruction
TL;DR: A novel parameterized variety based model is presented that integrates these different domains into one common framework to accommodate multi-view stereo for multiple exposure input views and to render photo-realistic HDR images from arbitrary virtual viewpoints for high quality 3D reconstruction.