Amir Hossein Zabbah

Papers

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About

Amir Hossein Zabbah is an emerging researcher in the fields of autonomous systems and deep learning, with a focused interest in intelligent robotics and computer vision. His most-cited work, "Line Following Autonomous Driving Robot using Deep Learning" (2020), demonstrates a practical application of neural networks to enable a robot to autonomously navigate by following a painted line on the ground. In this study, Zabbah and his team collected extensive image and video data to train a deep neural network, bridging the gap between theoretical machine learning and real-world robotic control. This contribution highlights his ability to integrate data-driven approaches with embedded systems, offering a scalable solution for autonomous navigation in constrained environments. With 5 citations, this paper serves as a foundational reference for students and researchers exploring low-cost autonomous driving platforms. Zabbah’s work is particularly valuable for those interested in the intersection of robotics, deep learning, and edge computing, and it underscores his potential to contribute further to the development of intelligent, self-navigating machines.