Ebtisam Alabdulqader
Papers
1
Total Citations
23
H-Index
1
About
Dr. Ebtisam Alabdulqader is a leading researcher at the intersection of computer vision, artificial intelligence, and autonomous surveillance systems. Her primary contributions lie in advancing Human Activity Recognition (HAR) for drone-based platforms, where she has pioneered novel methodologies for interpreting complex human behaviors from aerial perspectives. Her most cited work, "Drone-Based Public Surveillance Using 3D Point Clouds and Neuro-Fuzzy Classifier" (2025), has already garnered 23 citations, reflecting its immediate impact on the field. In this study, Dr. Alabdulqader introduces a hybrid neuro-fuzzy framework that processes 3D point cloud data to classify human actions with remarkable accuracy, addressing critical challenges in video surveillance, sports analytics, and human-robot interaction. By integrating fuzzy logic with neural networks, her approach enhances interpretability and robustness in dynamic, real-world environments. This work stands out for its practical application to public safety and autonomous monitoring, offering a scalable solution for real-time threat detection and behavioral analysis. Dr. Alabdulqader’s research continues to shape the future of intelligent surveillance, bridging the gap between theoretical AI models and deployable drone technologies.
Research Focus
Key Achievements
Top Papers
- 1