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
Automated monocular vision based system for picking textureless objects
TL;DR: An Autonomous Machine Vision system which grasps a textureless object from a clutter in a single plane, rearranges it for proper placement and then places it using vision using a unique vision-based pose estimation algorithm, collision free path planning and dynamic Change-Over algorithm for final placement.
Proceedings ArticleDOI
Recommendation of complementary garments using ontology
TL;DR: A novel recommendation engine to suggest coordinated outfits to the users that complements each other that encodes subjective knowledge of clothing experts in Multimedia Web Ontology Language (MOWL) and makes use of evidential and causal reasoning scheme to deal with the media properties of concepts.
Proceedings ArticleDOI
An appearance based approach for video object extraction and representation
TL;DR: A scheme for organisation of video objects in an appearance based hierarchy is proposed using a new SVD based eigen-space merging algorithm that enables approximate query resolution.
Proceedings ArticleDOI
Probabilistic Approach for Correction of Optically-Character-Recognized Strings Using Suffix Tree
Rupi Jain,Santanu Chaudhury +1 more
TL;DR: An approach for correcting character recognition errors of an OCR which can recognise Indic Scripts and achieves maximum error rate reduction of 33% over simple character recognition system.
Proceedings ArticleDOI
Document indexing framework for retrieval of degraded document images
TL;DR: This paper presents a indexing methodology that uses multiple kernel learning to combine features from different modalities by joint optimization of search time and accuracy and is demonstrated on document images of Bangla and Devanagari script.