Georgios Triantafyllidis
Papers
7
Total Citations
206
H-Index
5
About
Georgios Triantafyllidis is a leading researcher in agricultural robotics and precision farming, with a focus on deep learning-based visual recognition for weed control. His most influential work, "Deep learning-based visual recognition of rumex for robotic precision farming" (2019), has garnered 95 citations, establishing him as a key figure in automated weed detection. Triantafyllidis introduced a novel framework combining advanced image features with linear representations for weed recognition (2016, 33 citations), significantly improving object categorization methods. His research extends to developing vision systems for robotic weed control in crops and grasslands, including a prototype robot that detects harmful Broad-leaved dock in dairy farm grasslands using real-world field data (2018, 16 citations). Beyond agriculture, Triantafyllidis contributed to medical robotics through the OTELO project, designing user interfaces for mobile tele-echography systems (2005, 26 citations). His work bridges precision agriculture and robotic telemedicine, demonstrating versatility in applying computer vision to real-world challenges. With over 200 total citations, Triantafyllidis continues to advance autonomous systems for sustainable farming and remote healthcare.
Research Focus
Key Achievements
Top Papers
- 1
- 2Weed recognition framework for robotic precision farming33 citations · 2016
- 3Image-based recognition framework for robotic weed control systems29 citations · 2017
- 4Mobile tele-echography: user interface design26 citations · 2005
- 5
- 6Vision System for Robotized Weed Recognition in Crops and Grasslands5 citations · 2017
- 7A user interface for mobile robotized tele-echography2 citations · 2006