Papers
6
Total Citations
25
H-Index
3
About
Mohammad Al Hasan is a leading researcher at the intersection of agricultural robotics, computer vision, and precision farming. His primary contributions lie in developing autonomous navigation systems for agricultural robots, with a focus on real-time crop row detection and weed management. His most-cited work, "Real-time crop row detection using computer vision- application in agricultural robots" (2024, 11 citations), addresses the challenge of enabling robots to navigate variable field conditions, such as changing weather and crop growth stages. He further advances smart farming with his semi-autonomous IoT robot (2023, 6 citations), designed to modernize traditional agriculture in developing regions like Bangladesh. Hasan’s innovative approach includes decision-level multi-sensor fusion, as seen in his 2025 study on weed detection for corn production, which enhances classification accuracy beyond single-camera systems. He has also explored networked control systems and multi-agent robot formations, demonstrating versatility in robotics and control theory. With a growing citation impact, Hasan’s work is pivotal for sustainable, automated agriculture, offering practical solutions for global food security.
Research Focus
Key Achievements
Top Papers
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- 5Optimal filtering in multi-agent robots using leader-follower formation2 citations · 2014
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