Noor Fadel

University of Babylon

Papers

2

Total Citations

11

H-Index

2

About

Noor Fadel is a researcher at the forefront of human-computer interaction (HCI), specializing in computer vision and machine learning for hand gesture recognition. Her work addresses the critical challenge of enabling intuitive, natural communication between humans and machines. Fadel’s most cited paper, the 2023 survey "Computer Vision Techniques for Hand Gesture Recognition," has garnered 7 citations, establishing a comprehensive foundation for the field. Her 2022 study, "Detecting Hand Gestures Using Machine Learning Techniques," with 4 citations, advances practical detection methods, underscoring the growing demand for seamless HCI. By synthesizing and advancing techniques in gesture interpretation, Fadel’s research directly impacts applications in assistive technology, virtual reality, and contactless interfaces. Her contributions are pivotal in driving the transition from traditional input devices to gesture-based control, making her a key voice in the evolution of interactive systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
11
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Computer Vision Techniques for Hand Gesture Recognition: Survey
7 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 1
🏛 Institutions: University of Babylon

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 5 days ago