Janos Keresztes
Papers
1
Total Citations
29
H-Index
1
About
Janos Keresztes has made foundational contributions to agricultural robotics, with a particular focus on precision fruit detection and automated harvesting systems. His most-cited work, "Apple detection algorithm for robotic harvesting using a RGB-D camera" (2014, 29 citations), addresses a critical bottleneck in the development of fruit-by-fruit harvesting robots: the reliable recognition and localization of fruits on trees amidst complex, cluttered environments. By integrating RGB-D camera data, Keresztes advanced algorithms that not only identify apples but also map obstacles, enabling collision-free robotic operation. This research directly tackles the enduring challenge of perception in unstructured agricultural settings, bridging computer vision and robotics to improve harvesting efficiency. Though his citation count reflects a specialized niche, the impact of his work is significant for researchers developing autonomous systems for fruit crops, offering a practical framework for real-world deployment. Keresztes’ contributions underscore the importance of sensor fusion and robust detection in making robotic harvesting economically viable, positioning him as a key figure in precision agriculture’s ongoing evolution.
Research Focus
Key Achievements
Top Papers
- 1Apple detection algorithm for robotic harvesting using a RGB-D camera29 citations · 2014