Adriana Carrillo Rios
Papers
1
Total Citations
21
H-Index
1
About
Adriana Carrillo Rios is a researcher specializing in computer vision and robotics, with a focus on real-time object detection algorithms. Her most cited work, "Comparison of the YOLOv3 and SSD MobileNet v2 Algorithms for Identifying Objects in Images from an Indoor Robotics Dataset" (2021), has garnered 21 citations, establishing a benchmark for evaluating lightweight detection models in constrained environments. This study systematically compares two leading algorithms—YOLOv3 and SSD MobileNet v2—assessing their speed and accuracy for indoor robotic applications, providing critical insights for deploying efficient vision systems on resource-limited platforms. Carrillo Rios’s contributions are particularly valuable for advancing autonomous navigation and human-robot interaction, where rapid and reliable object identification is essential. Her work bridges the gap between algorithm performance and practical robotics, offering a foundation for future optimizations in embedded vision. By highlighting the trade-offs between detection speed and precision, she has helped guide researchers in selecting appropriate models for specific robotic tasks. Carrillo Rios continues to explore how computer vision can enhance robotic perception, making her research highly relevant for students and engineers developing intelligent, real-world systems.
Research Focus
Key Achievements
Top Papers
- 1