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 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
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 |
---|
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 |
---|
Modules | Credits | TAF | SSD |
---|
Modules | Credits | TAF | SSD |
---|
Modules | Credits | TAF | SSD |
---|
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.
Pattern recognition and Signal and image Processing in Bioinformatics - SEGNALI E IMMAGINI I (2020/2021)
Teaching code
4S008228
Credits
6
Coordinator
Not yet assigned
Language
Italian
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
To show the organization of the course that includes this module, follow this link: Course organization
The teaching is organized as follows:
Teoria
Laboratorio
Learning outcomes
The course aims at providing the students with the fundamentals of signal and image processing with emphasis on aspects that are relevant in the field of bioinformatics at both theoretical and practical levels. At the end of the course the students will be able to analyze the typical signal and image processing problems encountered in bioinformatics as well as to devise and implement suitable solutions grounding on the knowledge gained in the theory sessions and using the main available toolboxes.
Program
THEORY
The theory part aims at providing the students with all the theoretical aspects that are needed for understanding, analyzing and solving the main signal and image processing issues that are encountered in the field of bioinformatics.
The course contents include the mathematical foundations, methodological tools and algorithms that are required in this respect and will be complemented by exercise sessions.
SYLLABUS
Introduction to signals and systems with special focus on the biomedical and bioinformatics fields
Linear Time Invariant Systems (LTIS): continuous and discrete time, properties, zero-input, zero-state, impulse response, transfer function, system stability, analysis of system behavior
Fourier Transform (FT): Fourier Series, Continuous and Discrete time FT, Discrete Fourier Transform (DFT)
Filtering: analog and digital, low-pass, high-pass, in time and frequency domain, linear and non-linear, 1D and 2D
A/D signal conversion: sampling and quantization of signals and images
Image segmentation: edge-based and region-based main segmentation algorithms
Texture analysis by Gabor filters and basics of time/frequency and multiscale analysis
Feature extraction in time/space and frequency and application examples in the field of pattern recognition
Please note that all the methods are meant to be applied to both signals and images unless differently specified.
LABORATORY SESSIONS
Laboratory sessions at getting familiar with the main algorithms and tools introduced in the theoretical sessions by solving some typical signal and image processing problems.
Examination Methods
The exam of the SIGNAL AND IMAGE PROCESSING module consists in questions concerning the topics of both the theory and the laboratory sessions, with respective weight of 2/3 and 1/3, and one exercise (15 punti). In case the exam would be in teleconference mode it would be in oral form.
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 soon also via the Univr app.
Graduation
List of theses and work experience proposals
Stage | Research area |
---|---|
Correlated mutations | Various topics |
Attendance
As stated in the Teaching Regulations for the A.Y. 2022/2023, attendance at the course of study is not mandatory.