Vassilios Morellas
Papers
7
Total Citations
135
H-Index
5
About
Vassilios Morellas is a leading researcher at the intersection of computer vision, robotics, and precision agriculture. His work spans three key domains: agricultural technology, robotic perception, and motor skill learning. In precision agriculture, Morellas developed a groundbreaking methodology for detecting nitrogen deficiency in corn fields using high-resolution RGB imagery (51 citations), enabling farmers to deploy fertilizers more efficiently with both financial and environmental benefits. His contributions to robotics include pioneering algorithms for accurate 3D ground plane estimation from a single image (39 citations), which advanced landmark localization for SLAM problems. Morellas also made early contributions to neural network learning for robot arm inverse kinematics (22 citations), and more recently explored robotic embodiment of human-like motor skills through reinforcement learning as part of the innovative "Internet of Skills" framework. His work on feature-based covariance matching for multi-robot following (7 citations) addresses challenges in autonomous team applications. With publications spanning from 2002 to 2022, Morellas demonstrates sustained impact across computer vision, robotics, and agricultural automation, making his research particularly valuable for students interested in applying AI to real-world systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Accurate 3D ground plane estimation from a single image39 citations · 2009
- 3
- 4Robotic Embodiment of Human-Like Motor Skills via Reinforcement Learning11 citations · 2022
- 5
- 6Active Constrained Clustering via non-iterative uncertainty sampling3 citations · 2016
- 7