Papers
5
Total Citations
95
H-Index
3
About
Asim Khan is at the forefront of agricultural robotics and precision farming, where his work is reshaping how technology meets crop production. His research centers on developing intelligent, vision-driven systems for automated plant care, with a particular focus on robotic pollination and disease management. Khan’s comprehensive review on precision spraying for agricultural robots has garnered 61 citations, establishing a foundational resource for the field. He introduced TomFormer, a transformer-based deep learning model for early and accurate detection of tomato leaf diseases, achieving 12 citations for its innovative approach. His work extends to real-time diagnosis of strawberry foliar diseases and the use of deep learning to detect tomato flowers and buds in greenhouses, enabling robotic gantry systems to perform precise pollination. By integrating computer vision with robotic arms, Khan addresses critical challenges in reducing labor dependency and preserving costly pollen. His contributions are driving the shift toward smart farming, offering scalable, non-invasive solutions that enhance crop productivity and disease management in both open fields and controlled environments.
Research Focus
Key Achievements
Top Papers
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- 3Early and Accurate Detection of Tomato Leaf Diseases Using TomFormer12 citations · 2023
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- 5Early and Accurate Detection of Tomato Leaf Diseases Using TomFormer2 citations · 2023