Asst. Marija Ivanovska, MSc.
Assistant
Laboratory of Machine Intelligence (LMI)
Faculty of Electrical Engineering, University of Ljubljana
Tržaška cesta 25
Si-1000 Ljubljana, Slovenia
Tel.: +386 1 4768 841
Fax.: +386 1 4768 316
E-mail: marija.ivanovska@fe.uni-lj.si
64622 Signal Analysis [Undergraduate Course]
This course provides a foundational understanding of signal processing, focusing on practical applications. Students learn to represent and analyze deterministic signals in time and frequency domains. The course emphasizes understanding various signal types, their properties, and processing methods.
64125 Signals [Undergraduate Course]
This course delves into the analysis and manipulation of signals, encompassing both theoretical foundations and practical applications. Students gain an understanding of how to represent and analyze signals—both deterministic and random—in time and frequency domains. The course emphasizes the classification of various signal types, their properties, and processing methods.
64206 Computer Vision [Master Course]
This course offers a comprehensive introduction to the fundamental concepts, theories, algorithms, and applications of computer vision. The main objective is to to equip students with a solid understanding of computer vision principles, enabling them to analyze and develop systems that interpret visual information. The course provides a balanced mix of theoretical knowledge and practical skills, preparing students for advanced studies or careers in fields where computer vision is applicable.
64250 Artificial Intelligence Systems [Master Course]
This course aims to provide students with a comprehensive understanding of the fundamental mathematical and computational approaches to artificial intelligence (AI). Students will explore the concepts of AI systems and examine real-world implementations. The course is ideal for students interested in the practical applications of AI, including expert systems, machine learning, and multi-agent systems.
64276 Advanced Computer Vision Methods [Master Course]
This course introduces students to advanced imaging technologies and methods used for image acquisition, processing, and analysis across a variety of domains including industry. A key focus of the course is on deep learning-based image analysis. Students gain practical experience by designing and training convolutional neural networks (CNNs) for image classification and segmentation tasks using modern deep learning frameworks.
64277 Intelligent Audio and Speech Systems [Master Course]
This course introduces students to the field of audio and speech technologies, encompassing the development and application of algorithms and techniques for processing and understanding audio signals, including human speech. It emphasizes both theoretical foundations and practical implementations. A special focus is given to the application of neural networks in the field of audio and speech signals.
Literature:
- [Source in Slovene] Signal Analysis – Solved Math Problems; Marija Ivanovska, Vitomir Štruc; 2020 [Link]