D. Kaleeswaran
Papers
1
Total Citations
1
H-Index
1
About
D. Kaleeswaran is a researcher at the forefront of computer vision and agricultural automation, with a primary focus on applying deep learning to real-world detection challenges. Their most influential work centers on the development of robust fruit and vegetable detection systems using the YOLO algorithm, a critical component for robotic harvesting platforms. Kaleeswaran’s key contribution lies in addressing the formidable environmental obstacles that plague automated recognition—such as shifting sunlight, leaf and branch occlusion, fruit clustering, and variable shadows—which have historically made accurate detection in unstructured agricultural settings extremely difficult. By engineering solutions that enhance YOLO’s performance under these complex, uneven conditions, their research directly advances the feasibility of precision agriculture and autonomous harvesting. With their 2023 paper on this topic already garnering citations, Kaleeswaran’s work is establishing a foundation for more resilient, field-ready computer vision systems. Their efforts are not only pushing the boundaries of object detection but also bridging the gap between algorithmic research and practical, deployable technology in the agricultural sector.
Research Focus
Key Achievements
Top Papers
- 1Fruits and Vegetables Detection using YOLO Algorithm1 citations · 2023