Tomoya Suyama
Papers
1
Total Citations
42
H-Index
1
About
Tomoya Suyama is a researcher at the forefront of agricultural robotics, specializing in the integration of deep learning for autonomous field operations. His primary research focuses on computer vision and intelligent control systems for agricultural machinery, with a particular emphasis on obstacle detection and collision avoidance. Suyama’s most influential work, "Implementation of deep-learning algorithm for obstacle detection and collision avoidance for robotic harvester" (2020), has garnered 42 citations, establishing a foundational approach for safe, real-time navigation in complex farming environments. This contribution is critical for advancing fully autonomous harvesters, addressing key safety and efficiency challenges in precision agriculture. By combining convolutional neural networks with robotic control, Suyama has helped bridge the gap between theoretical AI and practical, deployable farm technology. His work is notable for its direct application to reducing human oversight in hazardous harvesting tasks, marking a significant step toward scalable, intelligent agricultural systems.
Research Focus
Key Achievements
Top Papers
- 1