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..
For the year 2008/2009 No calendar yet available
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.
The Study plan 2008/2009 will be available by April 2nd. While waiting for it to be published, consult the Study plan for the current academic year at the following link.
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 (2009/2010)
Teaching code
4S02803
Teacher
Coordinator
Credits
6
Also offered in courses:
- Pattern Recognition of the course Masters in Intelligent and Multimedia Systems
Language
Italian
Scientific Disciplinary Sector (SSD)
ING-INF/05 - INFORMATION PROCESSING SYSTEMS
Period
1st Semester dal Oct 1, 2009 al Jan 31, 2010.
Learning outcomes
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.
Program
* 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 24 hours of laboratory.
Examination Methods
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.
Type D and Type F activities
Training offer to be defined
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.