The scientific article “Thermal Object Detection in Difficult Weather Conditions Using YOLO” by M. Kristo, M. Ivašić-Kos, M. Pobar was published in journal IEEE Access, 2020, vol. 8, 125459-125476, DOI: 10.1109/ACCESS.2020.3007481 and is available online.
Laboratory for Computer Vision, Virtual and Augmented reality
As part of the Young Scientists Career Development Project, a post-doctoral position has been approved for four years to participate in the RAASS project and to do its doctoral dissertation under the mentorship of Assoc. Marinas Ivasic-Kos
The scientific article “Active Player Detection in Handball Scenes Based on Activity Measures” by M. Pobar, M. Ivašić-Kos was published in open access in the journal MDPI Sensors, in the special issue “Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments ”, Sensors 2020, 20 (5), 1475 and is available […]
Netokracija on the participation of AIRI members Sanda Martinčić-Ipšić and Marina Ivašić Kos in Women in Data Science 2020 conference in Zagreb.
Marina Ivasic-Kos has participated in the 3rd edition of Women in Data Science – WiDS 2020 conference and presented the results of the RAASS project: Automatic recognition and analysis of the activities of athletes in handball scenes. More about the event was published at https://www.netokracija.com/treci-women-in-data-science-zagreb-164990
Marina Ivasic-Kos and Kristina Host participated in the 9th International Conference on Pattern Recognition Applications and Methods – ICPRAM 2020 held on 22-24. February 2020, in Valletta, Malta. They presented the paper “Tracking handball players with the DeepSORT algorithm”. Marina Ivasic-Kos was also the leader of the Data Mining and Algorithms for Big Data section.
Recently, one of the most active research area in computer vision is crowded scene analysis. A crowd can be defined as a mass of people or large group of individuals gathered in the same physical environment. Crowd modelling, crowd scene analysis and behavioural recognition are one of most challenging topics in computer vision and more […]
Multimedia content such as digital images and video have become an important storage and exchange media. A large amount of such content from competitions, games and training sessions is constantly being created in the sports domain, and there has been a great interest for multimedia content analysis among athletes and coaches, on all levels from […]
Highlights Multi-label classification and knowledge-based approach to image annotation. The definition of the fuzzy knowledge representation scheme based on FPN. Novel data-driven algorithms for automatic acquisition of fuzzy knowledge. Novel inference based algorithms for annotation refinement and scene recognition. A comparison of inference-based scene classification with an ordinary approach.
In this paper, a model for multi-level image annotation that is performed in two phases is proposed. In the first phase, a Naïve Bayes classifier is used to classify low-level image features into elementary classes. In the second phase, a knowledge representation scheme based on Fuzzy Petri Net is used to expand the level of […]