Daniil Zelinskyi
Papers
1
Total Citations
12
H-Index
1
About
Daniil Zelinskyi is a researcher at the forefront of real-time optical detection and tracking systems for unmanned aerial vehicles (UAVs). His primary research areas encompass high-performance computing architectures, computer vision, and robotic telescope control. Zelinskyi’s major contribution is the development of a groundbreaking parallel architecture that enables low-latency UAV detection and tracking using robotic telescopes. This system, detailed in his most-cited 2024 paper (12 citations), synergistically combines an accurate deep learning object detector with a fast object tracker operating in parallel, achieving real-time performance. By addressing the critical challenge of processing speed, his work has significant implications for security, surveillance, and airspace management. The innovative multi-threaded design not only enhances detection accuracy but also ensures the system can track fast-moving aerial targets without latency. With his work already gaining traction in the field, Zelinskyi is establishing himself as a key innovator in applied computer vision and autonomous surveillance systems.
Research Focus
Key Achievements
Top Papers
- 1