Hira Ansar
Papers
2
Total Citations
58
H-Index
2
About
Hira Ansar is a rising researcher at the intersection of computer vision, human-computer interaction, and healthcare technology. Her work focuses on developing robust, real-time hand gesture recognition systems that bridge communication gaps and enhance medical applications. In her highly cited 2023 paper, "Robust Hand Gesture Tracking and Recognition for Healthcare via Recurrent Neural Network" (38 citations), she tackled the challenge of dynamic gesture recognition in complex environments, introducing symmetry-based tracking methods that significantly improve accuracy for human-computer interaction in clinical settings. Her follow-up work, "Hand Gesture Recognition for Characters Understanding Using Convex Hull Landmarks and Geometric Features" (20 citations), directly addresses the needs of the deaf and hard-of-hearing community by enabling sign language interpretation through novel convex hull and geometric feature extraction techniques. These contributions demonstrate her commitment to making assistive technologies more accessible and reliable. With her innovative approaches to gesture symmetry and landmark-based recognition, Ansar is establishing herself as a key voice in developing practical, inclusive computer vision systems that serve both medical and communication needs.
Research Focus
Key Achievements
Top Papers
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- 2