Assoc. Prof. dr. Danijel Skočaj
Associate Professor
T: +386 1 479 8225
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Office hours: Thursday, 13:00-14:00
Room: R2.57 - Kabinet
Description

Danijel Skočaj is an associate professor at the University of Ljubljana, Faculty of Computer and Information Science. He is the head of the Visual Cognitive Systems Laboratory.  His main research interests lie in the fields of computer vision, machine learning, and cognitive robotics. In the framework of basic and applied research, he's been developing and introducing new advanced methods of deep learning and computer vision for solving complex problems requiring processing of visual information. He is also interested in the ethical aspects of artificial intelligence, machine learning and robotics, and the influence of the development of these technologies on society. He's been lecturing the courses from the fields of computer vision, cognitive robotics, and deep learning. He has led or collaborated in a number of projects from these research areas, such as EU projects, national research projects as well as industry-funded applied projects. Through the research and development applied projects he's been facilitating the transfer of research findings into practical applications.

Awards
  • 2020: The Golden Plaque for exceptional contributions to the development of scientific, pedagogical or artistic endeavours, and for strengthening the reputation of the University of Ljubljana.
  • 2019: Special recognition for outstanding research achievement, Faculty of Computer and information science, UL
  • 2013, 2017, 2019: Best paper in the Pattern recognition session award, International Electrotechnical and Computer Science Conference ERK 2013, 2017, 2019, Portorož, Slovenia.
  • 2012: Award for exceptional scientific achievement in Republic of Slovenia in year 2011 (ARRS).
  • 2002: Best PhD paper award, 11th International Electrotechnical and Computer Science Conference ERK 2002, Portorož, Slovenia.
  • 2002: Best paper award, 26th Workshop of the Austrian Association for Pattern Recognition (ÖAGM/AAPR), Graz, Austria.

 

Awards of my students:

  • 2020: Special award for research work of postgraduate students at UL, Faculty of Computer and Information Science (Matej Dobrevski).
  • 2020, Prešeren Prize for Students of the University of Ljubljana for outstanding achievements in science and art (Jaka Šircelj).
  • 2013, 2019, Faculty Prešeren Prize, UL, Faculty of Computer and information Science (Klemen Istenič, Kristian Žarn).
Classes
Laboratory
Projects
Past projects
Publications

  • TABERNIK, Domen, SKOČAJ, Danijel. Deep learning for large-scale traffic-sign detection and recognition. IEEE transactions on intelligent transportation systems, ISSN 1524-9050. [Print ed.], Apr. 2020, vol. 21, no. 4, str. 1427-1440

  • TABERNIK, Domen, ŠELA, Samo, SKVARČ, Jure, SKOČAJ, Danijel. Segmentation-based deep-learning approach for surface-defect detection. Journal of intelligent manufacturing, ISSN 0956-5515, Mar. 2020, vol. 31, no. 3, str. 759-776

  • MAVER, Jasna, SKOČAJ, Danijel. EL: local image descriptor based on extreme responses to partial derivatives of 2D Gaussian function. Mathematical problems in engineering, ISSN 1563-5147, 2019, vol. 2019 

  • URŠIČ, Peter, LEONARDIS, Aleš, SKOČAJ, Danijel, KRISTAN, Matej. Learning part-based spatial models for laser-vision-based room categorization. The international journal of robotics research, ISSN 0278-3649. [Print ed.], 2017, vol. 36, no. 4, str. 379-402

  • SKOČAJ, Danijel, VREČKO, Alen, MAHNIČ, Marko, JANÍČEK, Miroslav, KRUIJFF, Geert-Jan M., HANHEIDE, Marc, HAWES, Nick, WYATT, Jeremy L., KELLER, Thomas, ZHOU, Kai, ZILLICH, Michael, KRISTAN, Matej. An integrated system for interactive continuous learning of categorical knowledge. Journal of experimental & theoretical artificial intelligence, ISSN 0952-813X. [Print ed.], 2016, vol. 28, no. 5, str. 823-848

  • TABERNIK, Domen, LEONARDIS, Aleš, BOBEN, Marko, SKOČAJ, Danijel, KRISTAN, Matej. Adding discriminative power to a generative hierarchical compositional model using histograms of compositions. Computer vision and image understanding, ISSN 1077-3142. [Print ed.], Sep. 2015, vol. 138, str. 102-113

  • RIDGE, Barry, LEONARDIS, Aleš, UDE, Aleš, DENIŠA, Miha, SKOČAJ, Danijel. Self-supervised online learning of basic object push affordances. International journal of advanced robotic systems, ISSN 1729-8814, 2015, vol. 12, str. 24-1-24-18

  • URŠIČ, Peter, TABERNIK, Domen, BOBEN, Marko, SKOČAJ, Danijel, LEONARDIS, Aleš, KRISTAN, Matej. Room categorization based on a hierarchical representation of space. International journal of advanced robotic systems, ISSN 1729-8814, 2013, vol. 10

  • VREČKO, Alen, LEONARDIS, Aleš, SKOČAJ, Danijel. Modeling binding and cross-modal learning in Markov logic networks. Neurocomputing (Amst.). [Print ed.], 2012

  • KRISTAN, Matej, LEONARDIS, Aleš, SKOČAJ, Danijel. Multivariate online kernel density estimation with Gaussian kernels. Pattern recogn.. [Print ed.], 2011, vol. 44, no. 10/11, str. 2630-2642

  • WYATT, Jeremy L., AYDEMIR, Alper, BRENNER, Michael, HANHEIDE, Marc, HAWES, Nick, JENSFELT, Patric, KRISTAN, Matej, KRUIJFF, Geert-Jan M., LISON, Pierre, PRONOBIS, Andrzej, SJÖÖ, Kristoffer, VREČKO, Alen, ZENDER, Hendrik, ZILLICH, Michael, SKOČAJ, Danijel. Self-understanding and self-extension : a systems and representational approach. IEEE trans. auton. ment. dev. (Print). [Print ed.], Dec. 2010, vol. 2, no. 4, str. 282-303

  • KRISTAN, Matej, SKOČAJ, Danijel, LEONARDIS, Aleš. Online kernel density estimation for interactive learning. Image vis. comput.. [Print ed.], Jul. 2010, vol. 28, no. 7, str. 1106-1116

  • SKOČAJ, Danijel, LEONARDIS, Aleš. Incremental and robust learning of subspace representations. Image vis. comput.. [Print ed.], 2008, vol. 26, no. 1, str. 27-38

  • SKOČAJ, Danijel, LEONARDIS, Aleš, BISCHOF, Horst. Weighted and robust learning of subspace representations. Pattern recogn.. [Print ed.], May 2007, vol. 40, no. 5, str. [1556]-1569

  • FIDLER, Sanja, SKOČAJ, Danijel, LEONARDIS, Aleš. Combining reconstructive and discriminative subspace methods for robust classification and regression by subsampling. IEEE trans. pattern anal. mach. intell., Mar. 2006, vol. 28, no. 3, str. 337-350. 

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