Why FINI? »Collaboration and innovation with a special focus on an individualized and student-centered approach.«
Mario Žganec is co-founder and CTO of Alpineon, a Slovenian RTD-performing SME specializing in developing state-of-the-art speech-technology and computer vision products. He received his PhD from the University of Ljubljana. He holds the Prince2 project management certificate. Coordinator of several complex RTD projects – InteliMO, BioID, ATRIS and over ten industrial product development projects. Head of research group, research supervisor to 2 PhD students. His areas of competence include speech and image technologies, pattern recognition, signal processing, hardware development, data processing, communication protocols, sensors and control systems. He authored and co-authored seven patents and more than 50 technical and scientific articles. Recipient of the Prešeren student award in 1990, and the award for Outstanding Research Achievements by the Slovenian Research Agency in 2011. Recipient of the Slovenian Ambassador of Privacy award in 2014 for best practices in privacy protection.
The course provides an overview of various architectures of microprocessor systems that can be found in every modern vehicle. They range from simple microcontrollers to multi-core multimedia microprocessors. How to select the most appropriate hardware and software components when designing a system?
The course introduces state-of-the-art image acquisition and processing techniques needed when designing intelligent systems that require complex environment perception. Security systems, robots, driver assistance systems – how do they acquire images from the environment? How do they extract useful information from these images?
Nowadays, sensors are not only simple transformers of physical quantities into electric signals: they are miniature computers equipped with sensing components and communication interfaces. The course explains what are the parts of intelligent sensors, how they function and describes their software – ranging from simple microsensors to complex sensors for detecting object in the environment.
The course focuses on measurements of physical quantities in automotive energetics: flow, pressure, position, temperature, torque, vibrations, gas concentration, electric current… How to select the most appropriate measurement method? How to reduce measurement errors? How to transfer the data into the central control unit?