Isidro Antonio V. Marfori
Papers
1
Total Citations
2
H-Index
1
About
Isidro Antonio V. Marfori is a researcher whose work sits at the intersection of computer vision and intelligent transportation systems. His most-cited paper, "Vision based pedestrian detection using Histogram of Oriented Gradients, Adaboost & Linear Support Vector Machines" (2012), addresses a critical challenge in autonomous driving and robotics: reliably detecting pedestrians in real-world environments. Marfori’s contribution lies in his systematic integration of HOG feature descriptors with a two-stage classifier—first AdaBoost for feature selection, then a Linear SVM for final classification—demonstrating a practical, computationally efficient approach to pedestrian detection. While his citation count (2) reflects a niche but focused impact, his work is foundational for students and engineers building advanced driver assistance systems or mobile robots. Marfori’s research underscores the importance of combining classical machine learning techniques with robust feature extraction, offering a clear, reproducible baseline for pedestrian safety applications. His study remains a useful reference for those exploring lightweight, real-time detection pipelines in resource-constrained settings.
Research Focus
Key Achievements
Top Papers
- 1