Abdulwahab Alazeb
Papers
5
Total Citations
122
H-Index
5
About
Abdulwahab Alazeb is a dynamic researcher specializing in computer vision, machine learning, and intelligent perception systems, with a particular focus on object detection, human interaction recognition, and gesture-based communication. His work sits at the intersection of deep learning and real-world applications, addressing critical challenges in autonomous systems, robotics, and human-computer interaction. Alazeb's most influential contribution, "Remote Intelligent Perception System for Multi-Object Detection" (2024), has garnered 65 citations, reflecting the field's enthusiasm for advanced scene classification in robotic environments. His research on human interaction recognition, leveraging Quadratic Discriminant Analysis combined with Hidden Markov Models, demonstrates a sophisticated statistical approach to behavioral interpretation in surveillance and social robotics contexts, earning 20 citations. Equally impactful is his work on hand gesture recognition for sign language understanding, offering meaningful technological support for the deaf community—also cited 20 times. Beyond these achievements, Alazeb has advanced multi-method fusion strategies for object detection and UNet-based segmentation architectures, collectively pushing boundaries in augmented reality, autonomous driving, and robotic navigation. His growing body of work signals an emerging voice in applied artificial intelligence, making his research essential reading for students exploring vision-driven intelligent systems.
Research Focus
Key Achievements
Top Papers
- 1Remote intelligent perception system for multi-object detection65 citations · 2024
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- 4Enhanced Object Detection and Classification via Multi-Method Fusion11 citations · 2024
- 5