Courses
Programming I lab (C)
The primary goal of this course is to introduce students to the foundational principles of structured programming and familiarize them with programming languages. Students will learn to design simple algorithms, write pseudocode, and program in the C language. The course combines theoretical instruction with hands-on laboratory practice to reinforce learning and practical application.
Programming II (C)
The primary objective of this course is to explore advanced concepts of the C programming language and their application in structured programming. Students will delve into topics such as pointers, string manipulation, input/output functions, and complex data structures. Additionally, they will gain hands-on experience by experimenting with various programming environments.
Digital image processing and applications
By the end of the course, students are expected to develop a solid understanding of the fundamental principles of digital image acquisition and processing, as well as basic image transformation methodologies. They will consolidate their knowledge of various optimization methods and gain the ability to analyze techniques for spatial segmentation, compression, and edge detection. Additionally, students will learn foundational methodologies for feature extraction and multiscale analysis, equipping them with essential skills in image processing.
MSc "Informatics & Telematics"
MPhil in "Computer Science and Informatics"
MSc "Applied Geoinformatics"
Computer vision
By the end of the course, students will have a comprehensive understanding of the fundamental principles of digital image analysis. They will strengthen their knowledge of various image transformation and optimization methods and develop the skills to analyze spatial segmentation and edge detection techniques. Additionally, students will gain a solid grasp of basic methodologies for feature extraction and consolidate their expertise in visual content analysis through the application of artificial intelligence and deep learning techniques.
Embedded systems, Computer Vision and Robotics
The course aims to introduce students to key concepts central to the 4th Industrial Revolution (Industry 4.0) and digital transformation. It focuses on the study, analysis, and practical application of modern methodologies and advanced technologies in the fields of machine vision, human-computer interaction, and embedded systems.
Machine learning
MSc "Informatics & Telematics"
Computer vision
By the end of the course, students will have a comprehensive understanding of the fundamental principles of digital image analysis. They will strengthen their knowledge of various image transformation and optimization methods and develop the skills to analyze spatial segmentation and edge detection techniques. Additionally, students will gain a solid grasp of basic methodologies for feature extraction and consolidate their expertise in visual content analysis through the application of artificial intelligence and deep learning techniques.
MPhil in "Computer Science and Informatics"
Embedded systems, Computer Vision and Robotics
The course aims to introduce students to key concepts central to the 4th Industrial Revolution (Industry 4.0) and digital transformation. It focuses on the study, analysis, and practical application of modern methodologies and advanced technologies in the fields of machine vision, human-computer interaction, and embedded systems.
