Papers
2
Total Citations
114
H-Index
2
About
Dheeraj Kumar is a pioneering researcher at the intersection of agricultural technology and safety engineering, whose work bridges cutting-edge computer vision with critical infrastructure protection. His most impactful contribution comes from the field of precision agriculture, where he developed smart harvesting solutions for capsicum crops using the YOLO deep learning architecture. This landmark 2024 study, which has already garnered 98 citations, demonstrates a comprehensive system capable of detection, segmentation, growth stage classification, counting, and real-time mobile identification—a significant leap toward autonomous farming. Kumar’s earlier work in mine safety and disaster management, though less cited with 16 citations, reveals a consistent commitment to applying modern tools for life-saving applications. His research trajectory shows a rare versatility, moving from underground hazard mitigation to above-ground crop monitoring, all while maintaining a focus on practical, deployable technologies. For students and researchers, Kumar exemplifies how deep learning can be harnessed for tangible societal benefit—whether ensuring food security through smarter agriculture or protecting miners through enhanced safety protocols. His growing citation count signals an emerging leader in applied computer vision.
Research Focus
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