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.

Type D and Type F activities

The educational activities of type D are chosen by the student, those of type F are further knowledge useful for entering the world of work (internships, soft skills, project works, etc.). According to the Didactic Regulations of the Course, some activities can be chosen and included autonomously in the booklet, others must be approved by a special committee to verify their consistency with the study plan. Type D or F educational activities can be covered by the following activities.

1. Teachings taught at the University of Verona.

Include the teachings listed below and/or in the Course Catalogue (which can also be filtered by language of delivery via Advanced Search).

Booklet entry mode: if the teaching is included among those listed below, the student can include it autonomously during the period in which the study plan is open; otherwise, the student must submit a request to the Secretariat, sending the form to carriere.scienze@ateneo.univr.it during the period indicated.

2. CLA certificate or language equivalency.

In addition to those required by the curriculum, the following are recognized:

  • English language: 3 CFUs are recognized for each level of proficiency above the one required by the course of study (if not already recognized in the previous course of study).
  • Other languages and Italian for foreigners: 3 cfu are recognized for each proficiency level starting from A2 (if not already recognized in the previous study cycle).

These cfu will be recognized, up to a maximum of 6 cfu in total, as type F if the teaching plan allows, or as type D. Additional elective credits for language knowledge may be recognized only if consistent with the student's educational project and if adequately justified.

Booklet entry moderequest the certificate or equivalency to the CLA and send it to the Student Secretariat - Careers for career entry of the exam, via email: carriere.scienze@ateneo.univr.it

3. Soft skills

Discover the training paths promoted by the University's TALC - Teaching and learning center, intended for students regularly enrolled in the academic year of course delivery https://talc.univr.it/it/competenze-trasversali

Booklet entry mode: the teaching is not expected to be included in the curriculum. Only after obtaining the Open Badge, the CFUs in the booklet will be automatically validated. The registration of CFUs in career is not instantaneous, but there will be some technical time to wait.  

4. Contamination lab 

The Contamination Lab Verona (CLab Verona) is an experiential course with modules on innovation and enterprise culture that offers the opportunity to work in teams with students from all areas to solve challenges set by companies and organisations.  

Upon completion of a CLab, students will be entitled to receive 6 CFU (D- or F-type credits).  

Find out more:  https://www.univr.it/clabverona 

PLEASE NOTE: In order to be admitted to any teaching activities, including those of your choice, you must be enrolled in the academic year in which the activities in question are offered. Students who are about to graduate in the December and April sessions are therefore advised NOT to undertake extracurricular activities in the new academic year in which they are not enrolled, as these graduation sessions are valid for students enrolled in the previous academic year. Therefore, students who undertake an activity in an academic year in which they are not enrolled will not be granted CFU credits.  

5. Stage/internship period

In addition to the CFUs required by the curriculum (check carefully what is indicated on the Didactic Regulationshere you can find information on how to activate the internship. 

Check in the regulations which activities can be Type D and which can be Type F.

Please also note that for traineeships activated after 1 October 2024, it will be possible to recognise excess hours in terms of type D credits, limited only to traineeship experiences carried out at host organisations outside the University.

 

Semester 1  From 10/1/24 To 1/31/25
years Modules TAF Teacher
1° 2° Introduction to smart contract programming for ethereum D Sara Migliorini (Coordinator)
1° 2° BEYOND ARDUINO: FROM PROTOTYPE TO PRODUCT WITH STM MICROCONTROLLER D Franco Fummi (Coordinator)
1° 2° APP REACT PLANNING D Graziano Pravadelli (Coordinator)
1° 2° HW components design on FPGA D Franco Fummi (Coordinator)
Semester 2 From 3/3/25 To 6/13/25
years Modules TAF Teacher
1° 2° LaTeX Language D Enrico Gregorio (Coordinator)
1° 2° Rapid prototyping on Arduino D Franco Fummi (Coordinator)
1° 2° Programming Challanges D Romeo Rizzi (Coordinator)
1° 2° Protection of intangible assets (SW and invention)between industrial law and copyright D Mila Dalla Preda (Coordinator)

Teaching code

4S012355

Credits

6

Also offered in courses:

  • Digital design of the course Master's degree in Computer Engineering for Robotics and Smart Industry

Language

English en

Scientific Disciplinary Sector (SSD)

ING-INF/05 - INFORMATION PROCESSING SYSTEMS

Period

Semester 2 dal Mar 3, 2025 al Jun 13, 2025.

Courses Single

Authorized

Learning objectives

The course aims to provide theoretical foundations and practical tools to address the problems of estimating the 3D structure of a scene starting from images, the data driven geometric and photometric 3D modeling of scenes, dynamic analysis of scenes. At the end of the course the student will have to demonstrate the ability to apply the acquired knowledge, in particular i) know ho to handle the diverse data structures used to model scenes and objects 3D, also to apply machine learning methods on them, ii) Know the method used for 3D scanning, vision-based tracking, photometric reconstruction. iii) use computational vision methods in various application scenarios, such as robotics or medical image processing; iv) manage issues of efficiency and accuracy of the techniques. At the end of the course the student will also have to show that he is able to continue his studies independently in the field of visual computing and the analysis of three-dimensional data. Must be able to present the results of a computational vision application and deal with professionals in the sector and have the ability to autonomously adapt to technical evolution and the state of the art in the field of computational vision.

Prerequisites and basic notions

Basic knowledge of image processing, linear algebra, computer vision

Program

3D reconstruction: data structures to represent surfaces and volumetric data, point clouds, meshing, surface recovery, implicit representations,
From 2D to 3D: motion estimation, tracking, structure from motion and SLAM, 3D scanning technologies
Reflectance modeling and materials characterization, Photometric Stereo
3D reconstruction from medical data
Fundamentals of geometry processing
Computational design and digital manufacturing

Bibliography

Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

Didactic methods

Written test on all teaching topics, through open questions and exercises, for a duration of 2 hours (maximum score 24/30) and homework evaluation (max 10/30) replaced by a project for non-attending students. There are no intermediate tests.

Learning assessment procedures

Written test on all teaching topics, through open questions and exercises, for a duration of 2 hours (maximum score 24/30) and homework evaluation (max 10/30) replaced by a project for non-attending students. There are no intermediate tests.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Evaluation criteria

To pass the exam, students must demonstrate to:
-have understood the concepts underlying the representation and processing of three-dimensional information, 3D scanning, the extraction and processing of surface geometry, the coding of attributes useful for graphic rendering and visualization, the reconstruction of geometric information for medical diagnosis from volumetric data;
-be able to present your arguments in a precise and organic way; know how to apply the knowledge acquired to solve application problems presented

Criteria for the composition of the final grade

The final grade will be the sum of the written evaluation and the practical test. The test is passed if the grade of the written test is higher than 14 and the grade of the practical test is higher than 4. If the sum of the scores is higher than 30, a score of 30 cum laude will be assigned.

Exam language

Inglese (italiano opzionale)

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