Suliman A. Alsuhibany

Papers

Total Citations

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About

Suliman A. Alsuhibany is a leading researcher in artificial intelligence, computer vision, and intelligent systems, with a focus on advancing autonomous technologies and scene understanding. His work has garnered significant attention, with his most-cited papers earning over 40 citations combined. Notably, his 2022 paper on "CNN Based Multi-Object Segmentation and Feature Fusion for Scene Recognition" (21 citations) introduces a deep learning framework that enhances multi-object recognition for applications like augmented reality, robotic navigation, and autonomous driving. This contribution is critical for enabling machines to interpret complex visual environments. In another highly cited 2022 study, "Object Detection Learning for Intelligent Self Automated Vehicles" (19 citations), Alsuhibany pioneers AI-driven object detection for smart city projects, integrating image processing and robotics to improve vehicular safety and efficiency. His research bridges theoretical advances in convolutional neural networks with practical implementations in autonomous systems, making him a key figure in the field. Alsuhibany’s work not only pushes the boundaries of computer vision but also directly impacts real-world technologies, from tourist guides to self-driving cars, solidifying his reputation as an innovator in intelligent automation.