| KEYWORD |
Video Synthetic Data for Machine Learning
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