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.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..

Academic year:
Definition of lesson periods
Period From To
Periodo zero Sep 19, 2005 Oct 10, 2005
1° Q - 2° anno e successivi Oct 3, 2005 Dec 2, 2005
1° Q - 1° Anno Oct 17, 2005 Dec 2, 2005
2° Q Jan 8, 2006 Mar 9, 2006
3° Q Apr 3, 2006 Jun 9, 2006
Exam sessions
Session From To
Exam period 0 Oct 17, 2005 Oct 21, 2005
Exam Session I Dec 12, 2005 Dec 23, 2005
Exam Session II Mar 20, 2006 Mar 31, 2006
Summer term Jun 19, 2006 Jul 28, 2006
Autumn term Sep 4, 2006 Sep 29, 2006
Degree sessions
Session From To
Extra term Dec 14, 2005 Dec 14, 2005
Winter term Mar 15, 2006 Mar 15, 2006
Summer term Jul 19, 2006 Jul 19, 2006
Autumn term Sep 13, 2006 Sep 13, 2006
Holidays
Period From To
All Saints Day Holiday Nov 1, 2005 Nov 1, 2005
Immaculate Conception Dec 8, 2005 Dec 8, 2005
Christmas holidays Dec 23, 2005 Jan 7, 2006
Easter holidays Apr 13, 2006 Apr 19, 2006
Liberation Day Apr 25, 2006 Apr 25, 2006
Labour Day holiday May 1, 2006 May 1, 2006
Saint's Day Holiday May 21, 2006 May 21, 2006
Day of the Republic Jun 2, 2006 Jun 2, 2006
Summer holidays Jul 31, 2006 Aug 31, 2006

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.

Exam calendar

Should you have any doubts or questions, please check the Enrolment FAQs

Academic staff

B C D F G M O P Q S

Belussi Alberto

alberto.belussi@univr.it +39 045 802 7980

Bonacina Maria Paola

mariapaola.bonacina@univr.it +39 045 802 7046

Caliari Marco

marco.caliari@univr.it +39 045 802 7904

Cristani Matteo

matteo.cristani@univr.it 045 802 7983

Cristani Marco

marco.cristani@univr.it +39 045 802 7841

De Marchi Stefano

stefano.demarchi@univr.it 045 8027978

Fiorini Paolo

paolo.fiorini@univr.it 045 802 7963

Fusiello Andrea

nome.cognome[at]uniud.it

Giachetti Andrea

andrea.giachetti@univr.it +39 045 8027998

Manca Vincenzo

vincenzo.manca@univr.it 045 802 7981

Mariotto Gino

gino.mariotto@univr.it +39 045 8027031

Mastroeni Isabella

isabella.mastroeni@univr.it +39 045 802 7089

Monti Francesca

francesca.monti@univr.it 045 802 7910

Morato Laura Maria

laura.morato@univr.it 045 802 7904

Murino Vittorio

vittorio.murino@univr.it 045 802 7996

Oliboni Barbara

barbara.oliboni@univr.it +39 045 802 7077

Pica Angelo

angelo.pica@univr.it

Posenato Roberto

roberto.posenato@univr.it +39 045 802 7967

Quaglia Davide

davide.quaglia@univr.it +39 045 802 7811

Segala Roberto

roberto.segala@univr.it 045 802 7997

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 enrolment year.

ModulesCreditsTAFSSD
ModulesCreditsTAFSSD
ModulesCreditsTAFSSD
ModulesCreditsTAFSSD
Un insegnamento a scelta tra le seguenti discipline fisiche affini

1° Year

ModulesCreditsTAFSSD

2° Year

ModulesCreditsTAFSSD

3° Year

ModulesCreditsTAFSSD

4° Year

ModulesCreditsTAFSSD
Un insegnamento a scelta tra le seguenti discipline fisiche affini
Modules Credits TAF SSD
Between the years: 4°- 5°Sette insegnamenti a scelta tra le seguenti discipline informatiche caratterizzanti
Between the years: 4°- 5°Un insegnamento nell'ambito affine Interdisciplinarità e applicazioni
5
C
ING-INF/04
5
C
ING-INF/04

Legend | 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.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S00072

Credits

5

The teaching is organized as follows:

Teoria

Credits

4

Period

3° Q

Academic staff

Vittorio Murino

Laboratorio

Credits

1

Period

3° Q

Academic staff

Vittorio Murino

Learning outcomes

Module: Theory
-------
The class aims at providing the basic theories and the most significant methods related to the analysis of data of whatever nature, that is theory and methods related to pattern recognition and machine learning.
This discipline is at the base and complete many other disciplines, recently of larger diffusion, like image processing, the analysis of huge quantities of data, artificial intelligence, databases, and many others.

In tha class, special emphasis will be devoted to the probabilistic and statistical techniques, in particular to the learning of systems for classification and recognition.

Many applications are involved by this discipline.
To quote some, image analysis and computer vision, data mining, bioinformatics, biomedical image and biological data analysis and interpretation (e.g., genomics, proteomics, etc.), biometry, video surveillance, robotics, speech recognition, and many others.


Module: Laboratory
-------
See description on the Theory part.

Program

Module: Theory
-------
* Introduction: what it is, what is useful for, systems, applications
* Recognition and classification
* Bayes theory
* Parameters' estimation
* Non parametric methods
* Linear classifiers, non linear classifiers, discriminant functions
* Feature estraction and selection, PCA and Fisher transform
* Expectation-Maximization e mixture of Gaussians
* Generative and discriminative methods
* Kernel methods e Support Vector Machines
* Artificial Neural Networks
* Hidden Markov Models
* Unsupervised classification (clustering)

In total, there are 32 hours of Theory lectures and 12 hours of laboratory.


Module: Laboratory
-------
The lab activities are done using the MATLAB environment.
See also description on the Theory part.

Examination Methods

Module: Theory
-------
An oral interview with 2 questions, aimed at verifying the understanding of theoretical concepts, and a project aimed at understanding the mastering of the mathematical and computer tools.
The oral test can be substituted with a written test with short questions similar to the oral one.
The exam is valid for 5 CFU, or 1 didactic unit.


Module: Laboratory
-------
See description on the Theory part.

Type D and Type F activities

Academic year:

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.

Further services

I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.