Mohammad A Hasan
Papers
1
Total Citations
4
H-Index
1
About
Mohammad A Hasan is a researcher at the forefront of precision agriculture and autonomous robotic navigation, with a specialized focus on computer vision and machine learning for agricultural applications. His most cited work, "Clustering Algorithm Based Straight and Curved Crop Row Detection Using Color Based Segmentation" (2021), addresses a critical challenge in field robotics: the accurate detection of crop rows under variable natural conditions. By developing a robust clustering algorithm that integrates color-based segmentation, Hasan’s method enables reliable identification of both straight and curved crop rows—a key capability for autonomous tractors and harvesters operating in real-world fields. This contribution has garnered 4 citations, reflecting its relevance to the growing field of agricultural automation. Beyond this paper, Hasan’s research explores the intersection of sensor data processing and intelligent control systems, aiming to reduce human intervention in farming. His work is particularly notable for tackling the inherent variability in crop row images caused by lighting, soil, and plant growth stages. For students and researchers interested in the practical deployment of AI in agriculture, Hasan’s studies offer a concrete example of how clustering and segmentation techniques can be adapted to solve real-world navigation problems, paving the way for more efficient and sustainable farming practices.
Research Focus
Key Achievements
Top Papers
- 1