Hemant Sharma

Swami Keshwanand Rajasthan Agricultural University

Papers

Total Citations

H-Index

About

Hemant Sharma is a researcher whose work bridges computer vision and agricultural innovation. His primary research areas include object detection and tracking in video, motion-based recognition, and the advancement of agricultural technology. Sharma’s most notable contribution is his 2017 paper on hybrid object detection, which combines improved three-frame differencing with background subtraction to enhance accuracy in video surveillance, robotics, and human-computer interaction. This work, cited 25 times, addresses a critical challenge in motion-based recognition by refining how systems detect objects in image sequences. In 2022, Sharma turned his focus to agricultural technology, publishing a study on the advancement of farming practices in India. This paper, with 8 citations, examines how modern innovations can replace conventional methods to boost productivity and sustainability in Indian agriculture. By synthesizing diverse inventions and materials, Sharma highlights pathways for improving food security and rural livelihoods. His dual contributions—enhancing machine vision and modernizing farming—demonstrate a versatile commitment to solving real-world problems through interdisciplinary research.