|SCIENTIFIC DISCIPLINARY SECTOR||ING-INF/03|
|MODULES||This unit is a module of:|
The course is aimed at providing machine learning basic and advanced techniques for data driven signal processing models to be used within autonomous systems design. In particular, perception and control modules in autonomous systems rely more and more on signal processing approaches whose parametrization can be learned from observing multimedia heterogeneous signals produced by the artificial system while performing specific tasks. The course analyses data acquisition and processing tradeoffs between edge and cloud resources on the basis of real-time, computational and energy consumption requirements. Specific attention will be devoted to high dimensional data processing on the edge (with real practical examples in Python), showing how deep learning approaches can be adapted and optimized for working with limited computational capabilities.
The student who has successfully followed the teaching of "Multimedia Signal Processing for Autonomous Systems" will be able to
In particular, during this teaching the student will learn to:
The lessons alternate theoretical explanations with practical exercises. Theoretical explanations are frequently exemplified with the analysis, execution, and debugging of code fragments directly on the teacher's PC. All the material seen in class (slides and practical examples) is shared through the AulaWeb and Teams platforms. Students can interact directly with the teacher during lessons or through the Teams platform.
The titles of the main contents discussed during frontal lessons are provided in the following list
Lectures slides (downloadable on AulaWeb)
Source code developed during the lectures (downloadable on AulaWeb and GitHub)
To learn more:
Students with learning disorders ("disturbi specifici di apprendimento", DSA) will be allowed to use specific modalities and supports that will be determined on a case-by-case basis in agreement with the delegate of the Engineering courses in the Committee for the Inclusion of Students with Disabilities.
Office hours: On request
SANDRO ZAPPATORE (President)
ROBERTO BRUSCHI (President Substitute)
All class schedules are posted on the EasyAcademy portal.
Development and presentation of a practical project work demonstrating how signal processing can be used to improve the autonomy of an artificial system.
The student who takes the "Multimedia Signal Processing for Autonomous Systems" exam is assigned a practical project to be solved through the implementation of signal processing algorithms by using one of the techniques described during the lectures. The implemented system should be able to increase the degree of autonomy of an artificial system by adding smart functionality to it. Through the analysis of the solution developed and presented by the student, it is verified at what level the fundamental concepts of autonomous systems have been understood, how these concepts have been applied for the implementation of the project, if the student is able to analyze and evaluate the functioning of the programs created and how the theoretical models studied in class are applied to design and create the required software. The evaluation of the exams is based on the effectiveness of the system implemented and its performance, on the quality of the project carried out and on the clarity of presentation.
|17/02/2023||09:00||GENOVA||Esame su appuntamento|
|15/09/2023||09:00||GENOVA||Esame su appuntamento|