Carlos Arturo Aguirre-Salado

Autonomous University of San Luis Potosí

Papers

1

Total Citations

11

H-Index

1

About

Carlos Arturo Aguirre-Salado is a researcher at the forefront of embedded systems and intelligent video processing. His work masterfully bridges the gap between hardware design and advanced algorithms, with a primary focus on developing low-power, real-time solutions for complex visual tasks. A key contribution is his pioneering integration of bio-inspired metaheuristics, such as the Honeybee Search Algorithm, into System-on-Chip (SoC) and FPGA architectures. This approach is exemplified in his highly cited 2022 paper on a "Low-Power Embedded System for Real-Time Video Tracking," which has garnered 11 citations for demonstrating a novel method to overcome the persistent challenges of computational efficiency and object detection in dynamic environments. By designing specialized hardware that mimics natural swarm intelligence, Aguirre-Salado has enabled robust video tracking for critical applications in robotics, unmanned vehicles, and industrial automation. His work stands as a significant achievement in making advanced computer vision both energy-efficient and practically deployable, addressing a core open problem in the field and paving the way for smarter, more autonomous systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
11
Total Citations
11
Avg Citations/Paper
🏆 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
11 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Autonomous University of San Luis Potosí

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago