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 |
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I sem. | Oct 3, 2016 | Jan 31, 2017 |
II sem. | Mar 1, 2017 | Jun 9, 2017 |
Session | From | To |
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Sessione invernale Appelli d'esame | Feb 1, 2017 | Feb 28, 2017 |
Sessione estiva Appelli d'esame | Jun 12, 2017 | Jul 31, 2017 |
Sessione autunnale Appelli d'esame | Sep 1, 2017 | Sep 29, 2017 |
Session | From | To |
---|---|---|
Sessione estiva Appelli di Laurea | Jul 19, 2017 | Jul 19, 2017 |
Sessione autunnale Appelli di laurea | Oct 18, 2017 | Oct 18, 2017 |
Sessione invernale Appelli di laurea | Mar 21, 2018 | Mar 21, 2018 |
Period | From | To |
---|---|---|
Festa di Ognissanti | Nov 1, 2016 | Nov 1, 2016 |
Festa dell'Immacolata Concezione | Dec 8, 2016 | Dec 8, 2016 |
Vacanze di Natale | Dec 23, 2016 | Jan 8, 2017 |
Vacanze di Pasqua | Apr 14, 2017 | Apr 18, 2017 |
Anniversario della Liberazione | Apr 25, 2017 | Apr 25, 2017 |
Festa del Lavoro | May 1, 2017 | May 1, 2017 |
Festa della Repubblica | Jun 2, 2017 | Jun 2, 2017 |
Vacanze estive | Aug 8, 2017 | Aug 20, 2017 |
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
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 |
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2° Year activated in the A.Y. 2017/2018
Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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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.
Machine Learning & Pattern Recognition (2016/2017)
Teaching code
4S02803
Teacher
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
ING-INF/05 - INFORMATION PROCESSING SYSTEMS
Period
II sem. dal Mar 1, 2017 al Jun 9, 2017.
Learning outcomes
Pattern Recognition (PR) focuses on creating classifiers, that is, algorithms that can learn aspects of the reality and make appropriate decisions once in the presence of new stimuli. Examples of classifiers are: speech recognition, automotive applications, surveillance systems, quality control systems, recommendation systems. The PR course intends to provide the methodological principles at the basis of the classification, together with the most modern techniques that can solve problems which were unmanageable until a few years ago. At the end of the course, the student will have to demonstrate how to solve a classification problem by applying the most suitable instrument to the case, justifying the theoretical choices.
Program
The course program can be divided into two parts, the methodological and the applicative one, which will go hand in hand with the lessons.
Methodologies
- Introduction: what is the classification, classification systems, and classification applications
- Statistical classification
- Bayesian decision theory
- Linear, non-linear and discriminative machines
--Selection and extraction of features, PCA and Fisher transform
--Parametric classifiers and how to train them
-- Expectation-Maximization Algorithm and Gaussian Mixtures
-- Non parametric classifiers and how to train them
--Hidden Markov Models
--Unsupervised classification methods (clustering)
Applications
-- Binary and multiclass classification on real benchmarks
-- Faces recognition
--Tracking
Textbooks:
- Richard O. Duda, Peter E. Hart, and David G. Stork. 2000. Pattern Classification (2nd Edition). Wiley-Interscience.
- Christopher M. Bishop. 2006. Pattern Recognition and Machine Learning (Information Science and Statistics). Springer-Verlag New York, Inc., Secaucus, NJ, USA.
Examination Methods
Examination method is oral; the required content will be those seen during the lessons, as indicated by the course program. In particular, when necessary, a formal demonstration of a procedure will be requested. In all cases, the questions will address a classification problem where the student will have to suggest the most suitable technique for the case, formally demonstrating the choice. The final vote will be built depending on the student's proposed solution to the question (20 points total), and the formal accuracy with which the solution is presented (10 points).
Teaching materials e documents
- Lab.1 Bayes Classifiers (zip, it, 6506 KB, 22/03/17)
- Lab.2 PCA (zip, it, 2 KB, 03/04/17)
- Lab.3 Eigenfaces (zip, it, 5046 KB, 05/04/17)
- Lab.4 Fisher Discriminant Analysis (zip, it, 2 KB, 19/04/17)
- Lab.5 Fisherfaces (zip, it, 5045 KB, 19/04/17)
- Lab.6 EM (zip, it, 16056 KB, 08/05/17)
- Lab.7 Stima non parametrica di densità - tracking (zip, it, 5 KB, 24/05/17)
- Lez.0 Introduzione al corso (zip, it, 514 KB, 06/03/17)
- Lez.1 Paradigma di Bayes (zip, it, 14941 KB, 06/03/17)
- Lez.2 Feature Extraction - PCA e FLDA (zip, it, 1698 KB, 26/04/17)
- Lez.3 ML estimation and EM algorithm (zip, it, 13228 KB, 02/05/17)
- Lez.4 Stima non parametrica e tracking (zip, it, 5773 KB, 10/05/17)
- Lez.5 Classificazione non supervisionata (zip, it, 2668 KB, 24/05/17)
Type D and Type F activities
Documents and news
- PIANO DIDATTICO LM-18 LM-32 (octet-stream, it, 17 KB, 21/09/18)
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 soon also via the Univr app.
Graduation
Deadlines and administrative fulfilments
For deadlines, administrative fulfilments and notices on graduation sessions, please refer to the Graduation Sessions - Science and Engineering service.
Need to activate a thesis internship
For thesis-related internships, it is not always necessary to activate an internship through the Internship Office. For further information, please consult the dedicated document, which can be found in the 'Documents' section of the Internships and work orientation - Science e Engineering service.
Final examination regulations
List of theses and work experience proposals
Attendance
As stated in the Teaching Regulations for the A.Y. 2022/2023, attendance at the course of study is not mandatory.