Cesar Puente

Autonomous University of San Luis Potosí

Papers

Total Citations

H-Index

About

Cesar Puente is a researcher specializing in embedded systems, computer vision, and robotics, with a focus on real-time video tracking and autonomous navigation. His work bridges hardware and software optimization, particularly through the integration of low-power SoC-FPGA platforms and bio-inspired algorithms. Puente’s most cited paper, "Design of a Low-Power Embedded System Based on a SoC-FPGA and the Honeybee Search Algorithm for Real-Time Video Tracking" (2022, 11 citations), introduces a novel approach to efficient object tracking, addressing challenges like power constraints and computational demands in robotics and unmanned vehicles. Another key contribution, "Vision-Based Humanoid Robot Navigation in a Featureless Environment" (2015, 10 citations), tackles the difficult problem of robot navigation in sparse or uniform surroundings, advancing autonomous systems’ adaptability. With a combined citation count of 21 across these works, Puente’s research demonstrates practical impact in automation and robotics. His achievements highlight a commitment to solving open problems in real-time vision systems, making his work valuable for students and researchers exploring low-power embedded solutions and intelligent navigation.