Juan C. Cuevas‐Tello
Papers
1
Total Citations
11
H-Index
1
About
Juan C. Cuevas‐Tello is a researcher whose work lies at the intersection of embedded systems, computer vision, and bio-inspired optimization. His key contributions focus on developing low-power, real-time solutions for complex computational problems, particularly in video tracking—a field he addresses as an open challenge due to obstacles like occlusion and dynamic environments. In his notable 2022 paper, "Design of a Low-Power Embedded System Based on a SoC-FPGA and the Honeybee Search Algorithm for Real-Time Video Tracking," he pioneered a novel approach that combines system-on-chip FPGA architecture with the Honeybee Search Algorithm, achieving efficient, real-time object tracking with minimal energy consumption. This work, which has garnered 11 citations, demonstrates his ability to bridge theoretical algorithms with practical hardware implementation, offering scalable solutions for robotics, unmanned vehicles, and automation. Cuevas‐Tello’s research is distinguished by its emphasis on energy efficiency and real-time performance, making his contributions particularly valuable for autonomous systems and edge computing applications.
Research Focus
Key Achievements
Top Papers
- 1