Zainal Rasyid Mahayuddin

Papers

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About

Zainal Rasyid Mahayuddin is a researcher whose work spans human-computer interaction, computer vision, and intelligent systems, with a particular focus on advancing how machines perceive and interpret the physical world. His early contributions explored gesture recognition using Microsoft Kinect, examining how controller-free environments could enable natural and efficient user-device communication across domains including research, surveillance, and medical applications — a paper that has garnered 17 citations and reflects his interest in intuitive human-machine interfaces. More recently, Mahayuddin has turned his attention to 3D object detection, a critical foundation for autonomous intelligent systems. His 2022 review on vision-based 3D object detection using deep learning — cited 15 times — provides a comprehensive analysis of methods, challenges, and future directions, highlighting how robust detection can transform robotics and autonomous vehicles by conveying object size, position, and orientation. This work was further extended in his 2023 study examining singular and multimodal detection techniques, which addresses the depth-information limitations of traditional 2D approaches and maps current advancements and research trajectories. Together, these contributions position Mahayuddin as a thoughtful synthesizer of emerging computer vision methodologies, offering valuable roadmaps for researchers and practitioners navigating this rapidly evolving field.