Ibtihal Razaq Niama ALRubeei

About

Dr. Ibtihal Razaq Niama ALRubeei is a leading researcher in artificial intelligence and computer vision, with a primary focus on gender recognition from facial images and its applications in human-computer interaction. Her most cited work, "Gender Recognition of Human from Face Images Using Multi-Class Support Vector Machine (SVM) Classifiers" (2023, 25 citations), addresses a critical challenge in robotics and security systems. By developing and refining multi-class SVM classifiers, Dr. ALRubeei has significantly advanced the accuracy and efficiency of automated gender recognition, a technology with broad implications for web search, surveillance, and interactive systems. Her contributions bridge the gap between theoretical machine learning and practical deployment, enabling more intuitive and secure human-robot interactions. With her work gaining traction in the research community, Dr. ALRubeei continues to push the boundaries of facial analysis, making her a notable figure in the field of intelligent systems. Her dedication to solving real-world problems through innovative algorithmic approaches underscores her impact on both academia and industry.

Research Focus

Key Achievements

Top Papers

1. 1
   Gender Recognition of Human from Face Images Using Multi-Class Support Vector Machine (SVM) Classifiers

   25 citations · 2023

Key Collaborators

Contact & Links