Refat Khan Pathan

Papers

Total Citations

H-Index

About

Refat Khan Pathan is a leading researcher in artificial intelligence, computer vision, and human-computer interaction, with a particular focus on biometric recognition and affective computing. His work bridges the gap between machine perception and human communication, developing robust systems for gender identification and facial expression recognition. Pathan’s highly cited 2020 paper on "Gender Recognition from Human Voice using Multi-Layer Architecture" (29 citations) introduced a novel method that significantly improved human-machine interaction, with applications spanning security systems, robotics, and call centers. His equally influential 2020 work on "Development of a Robust Multi-Scale Featured Local Binary Pattern for Improved Facial Expression Recognition" (21 citations) addressed critical limitations in traditional LBP methods, enhancing the accuracy of FER systems used in computer vision and dynamic texture recognition. By tackling the loss of neighboring pixel information—a key challenge in the field—Pathan’s multi-scale approach has advanced the reliability of emotion detection technologies. His contributions continue to shape the development of more intuitive, responsive AI systems, making him a notable figure in the evolution of intelligent, human-aware computing.