My present research interests include individual risk perception and risk taking, risk adaptation to increased safety margins, risk management within organizations, and training for individual mindfulness and organizational resilience.
Eriksson, H., Kovordányi, R., & Rankin, A. (2010). CRISIS--Virtual reality-based training for emergency management. TAMSEC 2010. (PDF)
Kovordányi, R. Rankin, A., & Eriksson, H. (2010). Foresight training as part of virtual-reality-based exercises for the emergency services. Presented at Crisis Management Training workshop, the 6th Nordic Conference on Human-Computer Interaction (NordiCHI 2010). (PDF)
Rankin, A. Kovordányi, R., & Eriksson, H. (2010). Episodic analysis for evaluating response operations and identifying training needs. Presented at Crisis Management Training workshop, the 6th Nordic Conference on Human-Computer Interaction (NordiCHI 2010). (PDF)
Kovordányi, R. and Roy, C. (2009). Cyclone Tack Forecasting Based on Satellite Images Using Artificial Neural Networks. ISPRS Journal of Photogrammetry & Remote Sensing, 64(6), 513-521. (PDF)
Kovordányi, R., and Roy, C. (2006). Cyclone forecasting based on satellite images using artificial neural networks. Accepted to SPIE, International Society for Optical Engineering 2006 Conference on Disaster Forewarning Diagnostic Methods and Management.
Roy, C., Kovordányi, R., Ahmed, R., Gumos, A., and Sivertun, Ĺ. (2006). Cyclone Tracking and Forecasting in Bangladesh Using Satellite Images without Supplementary Data. In proceedings of NordGIS 2006.
This line of research addresses simulator-based design and evaluation of advanced driver assistance systems (ADAS), with special focus on how drivers perceive risk in vehicles equipped with ADAS.
Kovordányi, R., Alm, T., and Ohlsson, K. (2006). Night-vision display unlit during uneventful periods may improve traffic safety. In Proceedings of 2005 IEEE Intelligent Vehicles Symposium. (PDF)
Alm, T., Kovordányi, R., and Ohlsson, K. (2006). Continuous versus situation-dependent night vision presentation in automotive applications. In Proceedings of 2006 HFES Annual Meeting of the Human Factors and Ergonomics Society. (PDF)
Kovordányi, R., Ohlsson, K., and Alm, T. (2005). Dynamically deployed support as a potential solution to negative behavioral adaptation. In Proceedings of 2005 IEEE Intelligent Vehicles Symposium. (PDF)
Alm, T., Ohlsson, K., and Kovordányi, R. (2005). Glass Cockpit Simulators - Tools for IT-based Car Systems Design and Evaluation. In Proceedings of the Driving Simulator Conference - North America, 2005. (PDF)
Kovordányi, R. (2005). When will advanced driver support systems be user-adaptive? The case of adaptive cruise control, in Proceedings of AAAI Spring Symposium Series, Challenges to Decision Support in a Changing World. (PDF)
Biologically-inspired neural networks
This line of research addresses the problem of how to achieve translation-invariance, that is, how to achieve a stable object representation in spite variations in the image. The biologically-based approach is to use local feature detectors in the first step, and then to combine and transform the detected features step-by-step across several stages of processing, in this way building up internal representations that are increasingly invariant with respect to position and size changes in the input image.
Saifullah, M., Kovordányi, R., and Roy, C. (2010). Error-driven learning vs. Hebbian learning in bidirectional hierarchical neural networks for image processing. In Proceedings of International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Application.
Kovordányi, R., Roy, C., and Saifullah, M. (2009). Local feature extraction--What receptive field size should be used? In proceedings of International Conference on Image Processing, Computer Vision and Pattern Recognition. (PDF)
Kovordányi, R., and Ohlsson, S. (2002). Toward adaptive support: Modelling drivers? allocation of attention. In Proceedings of the Twenty-fourth Annual Congress of the Nordic Ergonomic Society. (PDF)
Kovordányi, R. (2002). Sequencing of information versus interfacing between processing levels. Computational Intelligence, 18, 1, 47-49. (PDF)
Kovordanyi, R. (1999). Mental image reinterpretation in the intersection of conceptual and visual constraints. In Paton, R. and Neilson, I. (eds.): Visual representations and interpretation, chapter 4, 263-269. London: Springer Verlag. (PDF)
Kovordányi, R. (2001). Factorial modeling: A method for enhancing the explanatory and predictive power of cognitive models. In Altmann, E. M., Cleermans, A. Schunn, C. D. and Gray, W. D. (eds.): In Proceedings of the 2001 Fourth International Conference on Cognitive Modeling. Mahwah, NJ: Lawrence Erlbaum Associates. (PDF)
Kovordányi, R. (2000). Controlled exploration of alternative mechanisms in cognitive modeling. In Proceedings of the Twenty-Second Annual Meeting of the Cognitive Science Society. (PDF)
Kovordányi, R. (1999). Modeling and simulating inhibitory mechanisms in mental image reinterpretation--Towards cooperative human-computer creativity. Linkoping Studies in Science and Technology, Dissertation no. 589, Linkoping University.
Page responsible: Rita Kovordányi
Last updated: 2010-10-19