Arjun Upadhyay
Papers
7
Total Citations
160
H-Index
5
About
Arjun Upadhyay is an emerging researcher at the forefront of precision agriculture, specializing in robotic weed management, computer vision, and artificial intelligence-driven agricultural automation. His work addresses one of farming's most pressing challenges — sustainable, site-specific weed control — by developing intelligent systems that dramatically reduce herbicide dependency and environmental impact. Upadhyay's most influential contribution, a 2024 systematic review of ground robotic technologies for precision weed management (87 citations), has rapidly become a foundational reference in the field, synthesizing navigation systems, imaging sensors, and autonomous weed control strategies. Complementing this, his development of a deep learning-based smart sprayer using edge computing (27 citations) demonstrated real-world potential to minimize herbicide waste through targeted application. His multispecies weed-crop detection research employing advanced YOLO architectures across diverse field environments (26 citations) further showcases his expertise in building lightweight, deployable AI models for real-time agricultural use. Beyond detection, Upadhyay has contributed openly accessible weed-crop datasets and software interfaces for robotic platforms, accelerating community-wide progress. His research collectively spans mechanical and chemical weed control innovation, with grid-map-based systems showing herbicide savings of up to 80%. With over 160 cumulative citations across seven publications in just two years, Upadhyay represents a significant voice in the future of intelligent, sustainable farming.
Research Focus
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Top Papers
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