Md. Khaliluzzaman

International Islamic University Chittagong

Papers

Total Citations

H-Index

About

Md. Khaliluzzaman is a researcher in computer vision and deep learning, with a primary focus on human pose estimation and its applications in healthcare and rehabilitation. His most cited work, "Skeleton and Joint Angle Estimation Based on MobileNet" (2023), addresses the fundamental challenge of 2D pose estimation by detecting body key-points and generating skeletonized poses. This research is particularly significant for real-time applications, leveraging the efficiency of MobileNet to enable lightweight, deployable solutions for monitoring human movement. With 2 citations, this paper highlights his contribution to making pose estimation accessible for practical fields such as rehabilitation therapy and assistive healthcare technologies. Khaliluzzaman’s work bridges the gap between advanced computer vision techniques and real-world needs, offering scalable methods for analyzing joint angles and body dynamics. His research is valuable for students and practitioners interested in efficient deep learning models for human motion analysis, demonstrating how compact architectures can drive impactful applications in health monitoring and physical therapy.