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Dati Insegnamento
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Manifesto
Dati Insegnamento
Contesto
Anno Accademico 2023/2024
Corso di Studi Dott. - MI (1380) Ingegneria dell'Informazione / Information Technology
Anno di Corso 1

Scheda Insegnamento
Codice Identificativo 061636
Denominazione Insegnamento ADVANCED DEEP LEARNING MODELS AND METHODS FOR 3D SPATIAL DATA
Tipo Insegnamento MONODISCIPLINARE
Crediti Formativi Universitari (CFU) 5.0
Programma sintetico Nowadays deep learning spans multiple fields in science and engineering, from autonomous driving to human machine interaction, achieving human performance in solving many complex tasks, such as natural language processing and image recognition. This course presents recent advances in deep learning that brought data-driven models to achieve state-of-the-art performance in solving 3D vision problems. In particular, students will become acquainted with the biggest challenges of handling 3D data that are scattered in nature, thus are not suited for traditional filtering operations underpinning convolutional layers. The course will illustrate the most important layers for handling 3D data, as well as the neural networks for solving 3D Computer Vision problems and their application to Robotics and Computational Geometry. This is intended as an advanced course, thus proficiency in neural networks, convolutional neural networks and basic notions of optimization are assumed as pre-requirement to the participants.
Settori Scientifico Disciplinari (SSD) --

Dettaglio
Scaglione Nome Programma dettagliato
Da (compreso) A (escluso)
A ZZZZ Boracchi Giacomo, Magri Luca, Matteucci Matteo, Melzi Simone
manifestidott v. 1.10.0 / 1.10.0
Area Servizi ICT
22/06/2024