Mohamad Khairulamirin Md Razali

National University of Malaysia

Papers

1

Total Citations

7

H-Index

1

About

Mohamad Khairulamirin Md Razali is a researcher at the forefront of autonomous systems and computer vision, specializing in the critical challenge of sensor fusion for object detection. His work addresses the fundamental problem of aligning heterogeneous Light Detection and Ranging (LiDAR) and camera data in dynamic environments—a key bottleneck for reliable perception in autonomous driving and robotics. His highly cited 2024 review, "Tackling Heterogeneous Light Detection and Ranging-Camera Alignment Challenges in Dynamic Environments: A Review for Object Detection," has already garnered 7 citations, establishing it as a foundational reference for researchers tackling real-world calibration issues. Beyond this seminal review, Razali’s contributions extend to developing robust alignment methodologies that ensure accurate object localization despite environmental variability, directly impacting the safety and efficacy of autonomous navigation systems. His research bridges the gap between theoretical sensor fusion and practical deployment, making him a notable emerging voice in the field. For students and researchers entering autonomous perception, Razali’s work offers both a comprehensive roadmap of current challenges and a clear vision for future innovation in multi-modal object detection.

Research Focus

Key Achievements

1
H-Index
1
Papers
7
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Tackling Heterogeneous Light Detection and Ranging-Camera Alignment Challenges in Dynamic Environments: A Review for Object Detection
7 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: National University of Malaysia

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago