Mukesh Saraswat

Jaypee Institute of Information Technology

Papers

Total Citations

H-Index

About

Dr. Mukesh Saraswat is a leading researcher in intelligent systems and computational vision, with a primary focus on advancing healthcare applications through artificial intelligence. His work bridges the gap between machine learning and real-world medical imaging, particularly in the development of robust object classification and diagnostic tools. He has made significant contributions to the field of RGB-D object classification, introducing an enhanced bag-of-features approach that integrates a logarithmic spiral Henry Gas Solubility Optimization (HGSO) with a probability-based fuzzy Gaussian mixture model, achieving superior accuracy in complex visual environments. His research has garnered substantial attention, with his most cited work, "Congress on Intelligent Systems" (2021), accumulating 35 citations, underscoring its influence on the broader intelligent systems community. Dr. Saraswat has also co-edited the notable volume "Intelligent Vision in Healthcare" (2022), which has become a key reference for researchers exploring AI-driven medical diagnostics. His cumulative citation impact reflects a growing recognition of his innovative methodologies, positioning him as a pivotal figure in the evolution of intelligent vision systems for healthcare and beyond.