Debabrata Samanta
Papers
3
Total Citations
94
H-Index
3
About
Debabrata Samanta is a leading researcher at the intersection of computer vision, natural language processing, and intelligent document processing. His work focuses on solving critical challenges in automated document understanding, particularly for high-stakes industries like title insurance. Samanta’s most impactful contribution is his hybrid approach to document anomaly detection, which facilitates robotic process automation (RPA) in title insurance—a paper that has garnered 70 citations. He further advanced the field with a multi-modal framework for digital document stream segmentation, enabling efficient processing of heterogeneous document packages, a work cited 21 times. His innovative use of one-shot training for structured document retrieval, detailed in his paper on the Intelligent Information Retrieval Model (IIRM), demonstrates his ability to push boundaries with minimal data requirements. Samanta’s research has direct implications for automating complex, document-heavy workflows, reducing manual effort, and improving accuracy in sectors where document integrity is paramount. His work is essential reading for anyone interested in applied AI for document intelligence and enterprise automation.
Research Focus
Key Achievements
Top Papers
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