Yousri Ouerhani

Papers

Total Citations

H-Index

About

Yousri Ouerhani is a researcher specializing in computer vision, intelligent transportation systems, and road infrastructure analysis. His work focuses on developing automated methods for extracting and interpreting road markings from visual data, a critical component for autonomous vehicle navigation and road safety assessment. His most cited paper, "Road marking features extraction using the VIAPIX® system" (2016), introduces a novel approach that leverages the VIAPIX® imaging system to accurately detect and classify road markings under varying environmental conditions. This contribution addresses a key challenge in autonomous driving—reliable lane and sign detection—and has garnered 6 citations, reflecting its relevance in the field. Ouerhani's research bridges the gap between computer vision algorithms and practical transportation applications, offering robust solutions for real-world infrastructure monitoring. His work is particularly notable for its integration of hardware-software co-design, enhancing the precision of feature extraction in dynamic road scenes. For students and researchers, Ouerhani’s contributions underscore the importance of combining sensor technology with machine learning to advance intelligent mobility systems.