معرفی
Academician Professor Sven Lončarić serves as a Full Professor in the Department of Electronic Systems and Information Processing at the Faculty of Electrical Engineering and Computing, University of Zagreb. With his office located in room D-119 and contactable via phone at 6129-891, he maintains an active presence in both teaching and research activities within the institution. His work bridges theoretical computer science with practical applications across multiple domains.
Professor Lončarić's research spans computer vision, image processing, and deep learning with significant contributions to medical imaging, particularly in retinal analysis using optical coherence tomography. His work in color constancy and illumination estimation has advanced techniques for handling multi-illuminant scenes, while his research in ultrasound image analysis has practical applications in non-destructive testing. He also explores computer security aspects of machine learning models, particularly in backdoor detection and removal.
His recent publications demonstrate a strong trend toward applying deep learning techniques to solve complex problems in medical imaging, retail automation, and industrial applications. The concentration of work in retinal imaging and color constancy shows his commitment to advancing computer vision fundamentals while simultaneously addressing practical challenges in healthcare and industry. His research increasingly incorporates anomaly detection methods and robust security practices for machine learning systems.
Professor Lončarić actively contributes to the academic community through organizing events like the Croatian Computer Vision Workshop and the First Croatian Symposium on Artificial Intelligence, providing platforms for knowledge exchange in his fields of expertise. His work on astronomical data processing demonstrates the versatility of his methodological approaches across diverse scientific domains.
Within the Department of Electronic Systems and Information Processing, he participates in the Center of Excellence for Computer Vision, contributing to the institution's research profile in artificial intelligence and computer vision. His work on medical imaging applications connects the faculty with healthcare institutions, facilitating interdisciplinary collaborations that translate technical advances into medical practice.
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