Maha Abdulnasser
Papers
1
Total Citations
7
H-Index
1
About
Maha Abdulnasser is an emerging researcher in the fields of human-computer interaction, autonomous systems, and computer vision. Her most-cited work introduces a novel web-based hand gesture recognition model, validated through the implementation of a gesture-controlled omnidirectional autonomous vehicle. By leveraging a custom-trained YOLOv5s model, Abdulnasser’s system efficiently translates user hand gestures into precise control signals, demonstrating a practical, accessible approach to intuitive vehicle navigation. This contribution bridges the gap between real-time gesture recognition and autonomous mobility, offering a scalable solution for assistive technologies and smart transportation. With 7 citations to date, her research has already sparked interest in the integration of lightweight deep learning models with embedded systems. Abdulnasser’s work stands out for its emphasis on web-based deployment, reducing hardware dependency and broadening accessibility. As a forward-thinking innovator, she is paving the way for more natural, gesture-driven interfaces in autonomous robotics, making her a promising voice in the next generation of interactive and intelligent vehicle design.
Research Focus
Key Achievements
Top Papers
- 1