Fadzilah Hashim
Papers
2
Total Citations
8
H-Index
2
About
Dr. Fadzilah Hashim’s research lies at the intersection of computer vision, robotics, and intelligent control, with a focused expertise in mobile robot localization and orientation estimation. Her major contributions center on developing robust, vision-based methods for determining a robot’s position and orientation—a critical challenge for autonomous navigation. Notably, her 2009 work on “Estimation of mobile robot orientation using neural networks” (5 citations) pioneered a simple yet effective procedure that leverages neural networks to compute orientation from visual data, offering an alternative to complex sensor arrays. Complementing this, her 2008 study on “Active stereo vision based system for estimation of mobile robot orientation using affine moment invariants” (3 citations) introduced a stereo vision approach that uses affine moment invariants to achieve accurate pose estimation under varying viewpoints. These contributions demonstrate her ability to combine classical image processing with modern machine learning, providing practical solutions for real-world robotics. While her citation counts reflect a focused niche, her work has laid groundwork for subsequent advances in vision-guided mobile robots. Dr. Hashim’s research is particularly valuable for students and engineers seeking computationally efficient, vision-based localization techniques for autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Estimation of mobile robot orientation using neural networks5 citations · 2009
- 2