Yahya Alqahtani

Papers

Total Citations

120

H-Index

About

Yahya Alqahtani is a rising researcher at the forefront of intelligent aerial robotics and computer vision, with a focused expertise in developing deep learning systems for autonomous perception. His work centers on equipping Unmanned Aerial Vehicles (UAVs) with advanced neural network architectures to solve complex, real-world problems in surveillance, traffic management, and multi-object detection. Dr. Alqahtani’s most impactful contribution, "Remote intelligent perception system for multi-object detection" (2024, 65 citations), demonstrates his ability to enhance visual sensor analysis for robotic environments. He extends this work into dynamic settings with "UAV-based intelligent traffic surveillance using recurrent neural networks and Swin transformer" (2025, 19 citations), addressing urban congestion and safety through real-time adaptive decision-making. Further showcasing his depth, his research on "Unmanned aerial vehicle based multi-person detection via deep neural network models" (2025, 36 citations) tackles the unique challenges of motion blur in UAV-recorded video. With a growing body of highly cited work, Dr. Alqahtani is establishing himself as a key innovator in deploying intelligent, autonomous systems for safer and more efficient environments.