Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Academic calendar
The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
| Period | From | To |
|---|---|---|
| I semestre | Oct 1, 2018 | Jan 31, 2019 |
| II semestre | Mar 4, 2019 | Jun 14, 2019 |
| Session | From | To |
|---|---|---|
| Sessione invernale d'esame | Feb 1, 2019 | Feb 28, 2019 |
| Sessione estiva d'esame | Jun 17, 2019 | Jul 31, 2019 |
| Sessione autunnale d'esame | Sep 2, 2019 | Sep 30, 2019 |
| Session | From | To |
|---|---|---|
| Sessione Estiva | Jul 17, 2019 | Jul 17, 2019 |
| Sessione Autunnale | Nov 20, 2019 | Nov 20, 2019 |
| Sessione Invernale | Mar 17, 2020 | Mar 17, 2020 |
| Period | From | To |
|---|---|---|
| Sospensione dell'attività didattica | Nov 2, 2018 | Nov 3, 2018 |
| Vacanze di Natale | Dec 24, 2018 | Jan 6, 2019 |
| Vacanze di Pasqua | Apr 19, 2019 | Apr 28, 2019 |
| Festa del Santo Patrono | May 21, 2019 | May 21, 2019 |
| Vacanze estive | Aug 5, 2019 | Aug 18, 2019 |
Exam calendar
Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.
Should you have any doubts or questions, please check the Enrollment FAQs
Academic staff
mariacaterina.baruffi@univr.it
+39 045 802 7980
maurizio.boscaini@univr.it
alberto.burato@univr.it
rossana.capuani@univr.it
vittoria.cozza@univr.it
mila.dallapreda@univr.it
Study Plan
The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
| Modules | Credits | TAF | SSD |
|---|
Mathematical analysis 1
Computer Architecture
2° Year activated in the A.Y. 2019/2020
| Modules | Credits | TAF | SSD |
|---|
3° Year activated in the A.Y. 2020/2021
| Modules | Credits | TAF | SSD |
|---|
1 module to be chosen among the following| Modules | Credits | TAF | SSD |
|---|
Mathematical analysis 1
Computer Architecture
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
1 module to be chosen among the followingLegend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Signal and image processing (2020/2021)
Teaching code
4S000019
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
The teaching is organized as follows:
Teoria
Laboratorio [II turno]
Laboratorio [I turno]
Learning outcomes
The aim of this course is to provide the basic knowledge of methods and models for biomedical signal and image processing, developing the ability to analyze and solve problems of interest, mainly in the biomedical field. Each technique presented will be accompanied by applications on simulated and real signals.
At the end of the course, the student will be able to show knowledge of the main methods of biomedical signals and image processing. They will possess the ability to formulate, ana- lyze and solve problems of interest in bioengineering, through the acquired theoretical and practical basic knowledge. Finally, the student will be able to evaluate the traditional methods in the biomedical sciences in order to devise new approaches to methodological problems with clinical reversibility.
Program
- Introduction to the signal and image processing
- Preliminary mathematics
- Signals and their taxonomy
- Fourier analysis, 1D and 2D
- Methods for improving image quality (image enhancement) in both the spatial and frequency domains
- Extraction of image contours
- Extraction of image regions
- Morphological operators
- Representation and processing of color images
Examination Methods
Written with evaluation of Lab sessions.
Type D and Type F activities
Modules not yet included
Career prospects
Module/Programme news
News for students
There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and also via the Univr app.
Graduation
List of thesis proposals
| theses proposals | Research area |
|---|---|
| Analisi e percezione dei segnali biometrici per l'interazione con robot | AI, Robotics & Automatic Control - AI, Robotics & Automatic Control |
| Integrazione del simulatore del robot Nao con Oculus Rift | AI, Robotics & Automatic Control - AI, Robotics & Automatic Control |
| Domain Adaptation | Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Computer graphics, computer vision, multi media, computer games |
| Domain Adaptation | Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video) |
| BS or MS theses in automated reasoning | Computing Methodologies - ARTIFICIAL INTELLIGENCE |
| Domain Adaptation | Computing Methodologies - IMAGE PROCESSING AND COMPUTER VISION |
| Domain Adaptation | Computing methodologies - Machine learning |
| Dati geografici | Information Systems - INFORMATION SYSTEMS APPLICATIONS |
| Analisi e percezione dei segnali biometrici per l'interazione con robot | Robotics - Robotics |
| Integrazione del simulatore del robot Nao con Oculus Rift | Robotics - Robotics |
| BS or MS theses in automated reasoning | Theory of computation - Logic |
| BS or MS theses in automated reasoning | Theory of computation - Semantics and reasoning |
| Proposte di tesi/collaborazione/stage in Intelligenza Artificiale Applicata | Various topics |
| Proposte di Tesi/Stage/Progetto nell'ambito dell'analisi dei dati | Various topics |
Tutoring faculty members
Attendance modes and venues
As stated in the Teaching Regulations, attendance at the course of study is not mandatory.
Part-time enrolment is permitted. Find out more on the Part-time enrolment possibilities page.
The course's teaching activities take place in the Science and Engineering area, which consists of the buildings of Ca‘ Vignal 1, Ca’ Vignal 2, Ca' Vignal 3 and Piramide, located in the Borgo Roma campus.
Lectures are held in the classrooms of Ca‘ Vignal 1, Ca’ Vignal 2 and Ca' Vignal 3, while practical exercises take place in the teaching laboratories dedicated to the various activities.
