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Video Synthetic Data for Machine Learning

azienda Tesi esterna in azienda    


Parole chiave MACHINE LEARNING, MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS, SYNTHETIC DATA, VIDEO-PROCESSING

Riferimenti FABRIZIO RIENTE

Gruppi di ricerca VLSILAB (VLSI theory, design and applications)

Descrizione Vehicles become more connected and autonomous and the occupant experience inside the vehicle becomes even more important. From comfort to noise to the human machine interface, simulation plays a crucial role in engineering the safe and interactive passenger experience of the future. The Thesis goal is to combine Camera and Radar simulations allowing a virtual replication of the driving experience to create a synthetic dataset to train new Machine Learning models to recognize dangerous in-cabin situations.

Conoscenze richieste Python


Scadenza validita proposta 03/04/2025      PROPONI LA TUA CANDIDATURA