Paola Migneco
Traffic sign recognition algorithm: a deep comparison between Yolov5 and SSD Mobilenet.
Rel. Stefano Alberto Malan, Davide Faverato. Politecnico di Torino, Corso di laurea magistrale in Ict For Smart Societies (Ict Per La Società Del Futuro), 2024
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Abstract
One of the most intriguing and fascinating challenges of our century is the realization of the dream of making personal transportation a totally effortless experience. In this context, the reliability and accuracy of selected algorithms play a crucial role, as they enable vehicles to make immediate and accurate decisions, opening the door to a future of innovative transportation. The technical support provided by the MCA company has proved crucial to this project. The ultimate goal is the creation of a rover capable of moving autonomously, emulating fully autonomous driving, especially over rough terrain. This collaboration has allowed our research project to deepen the development of dedicated software for an embedded system that leverages artificial intelligence to perform object recognition and tracking, bringing with it promising prospects for transportation.
In the initial stages, we conducted a thorough analysis of existing code to identify common features and establish a solid foundation on which to further build our work
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