M. Buragohain
Papers
1
Total Citations
22
H-Index
1
About
M. Buragohain is a researcher at the forefront of agricultural robotics and deep learning, with a specialized focus on precision harvesting systems for horticultural crops. Their most impactful work centers on developing intelligent computer vision models for robotic fruit harvesting in complex orchard environments. Buragohain's key contribution is a pioneering two-stage deep-learning framework for detecting and classifying Kashmiri orchard apples, specifically designed to handle the critical challenge of fruit occlusion—a major bottleneck in automated harvesting. This model, detailed in their highly cited 2023 paper (22 citations), demonstrates a robust approach to identifying and grading apples even when partially hidden by leaves or branches, significantly advancing the feasibility of autonomous fruit picking in dense canopies. By integrating detection with occlusion-based classification, Buragohain’s research directly addresses a practical limitation that has hindered the deployment of agricultural robots in real-world orchards. Their work not only contributes to the growing field of smart agriculture but also provides a scalable solution for improving harvest efficiency and reducing labor dependency in regions like Kashmir, where apple cultivation is a vital economic activity.
Research Focus
Key Achievements
Top Papers
- 1