Harsh Nagar
Papers
4
Total Citations
117
H-Index
3
About
Harsh Nagar is a rising researcher at the forefront of agricultural robotics and deep learning, specializing in the application of computer vision to smart farming. His work centers on developing intelligent, real-time solutions for crop monitoring and autonomous harvesting, with a particular focus on precision agriculture. Nagar’s most impactful contribution is his pioneering use of the YOLO (You Only Look Once) object detection framework, as demonstrated in his highly cited 2024 paper on capsicum harvesting. This work, which has garnered 98 citations, introduces a comprehensive system capable of detection, segmentation, growth stage classification, counting, and real-time mobile identification—a significant leap toward fully automated horticulture. He has further advanced the field by integrating reinforcement learning with particle swarm optimization for trajectory planning in autonomous ground vehicles using 2D LiDAR point clouds (14 citations), and by applying YOLOv7 for robust cotton plant detection in challenging field conditions. His recent 2025 publication on climate-intelligent agriculture explores the synergy between robotic and UAV approaches for building resilient crop systems. Through these innovations, Nagar is establishing himself as a key contributor to the next generation of sustainable, data-driven farming technologies.
Research Focus
Key Achievements
Top Papers
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- 3Detection of Cotton Plants Using the YOLOv7 Deep Learning Model3 citations · 2023
- 4