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Wybrane pełne teksty z tego czasopisma
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Abstrakty
In this paper, the idea of rule extraciton from active contour classifiers is presented. The concepts are new in relation to active contour approach. The problem is illustrated by examples having roots in technical diagnosis and in analysis of content of images.
Czasopismo
Rocznik
Tom
Strony
73--86
Opis fizyczny
Bibliogr. 22 poz., il. kolor., rys.
Twórcy
autor
- Institute of Information Technology, Lodz University of Technology, ul. Wólczańska 215, 90-924 Łódź, Poland
autor
- Institute of Information Technology, Lodz University of Technology, ul. Wólczańska 215, 90-924 Łódź, Poland
Bibliografia
- [1] International Electrotechnical Commission - IEC, Interpretation of the Analysis of Gases in Transformers and other Oil-Filled Electrical Equipment in Service, 1979.
- [2] Pedrycz, W. and Szczepaniak, P., Digital Systems Design through Learning. In: New Learning Paradigms in Soft Computing., L.C. Jain and J.Kacprzyk (Eds.), Physica Verlag, c/o Springer-Verlag, Heidelberg, New York., 2001.
- [3] Rudnicki, M., Szczepaniak, P., and Cholajda, P., Genetic algorithm as a tool for solving electrical engineering problems. In: Evolutionary Algorithms in Engineering and Computer Science., chap. 13, K.Miettinen, P.Neittaanmaki and J.Periaux(Eds.), 1999, pp. 261-281.
- [4] Szczepaniak, P. and Cholajda, P., Genetic interpretation of DGA results in power transformers. In: Proc. Int. Conf. SSCC’98: Advances in Systems, Signals, Control and Computers., Vol. II, Burban, South Africa, 1998, pp. 216-220.
- [5] Szczepaniak, P., Fuzzy and Genetic Approach to Diagnosis of Power Transformers. In: Preprints of the 4th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes., Vol. 1, Budapest, Hungry, 2000, pp. 428-433.
- [6] Szczepaniak, P. and Sasiak, K., Zastosowanie adaptacyjnych sieci logicznych do diagnostyki transformatorow, Pomiary, automatyka, kontrola, Vol. 9, 2005, pp. 206-209, in Polish.
- [7] Szczepaniak, P. and Kłosi´nski, M., DGA-based Diagnosis of Power Transformers - IEC Standard versus k-Nearest Neighbours. In: IEEE Regon 8 SIBIRCON-2010, Proceedigs of 2010 IEEE Region 8 Int. Conference on Computional Technologies in Electrical and Electonic Engineering, Irkursk Listvyanka, Russia, 2010, pp. 740-743.
- [8] Szczepaniak, P., Advances in DGA-based Diagnosis of Power Transformers - Selected Techniques, Problemy Eksploatacji (Maintenance Problems), Vol. 2, 2011, pp. 189-199.
- [9] Kass, M., Witkin, W., and Terzopoulos, S., Snakes: Active Contour Models. Int. Journal of Computer Vision, Vol. 1, No. 4, 1988, pp. 321-333.
- [10] Grzeszczuk, R. and Levin, D., Brownian Strings: Segmenting Images with Stochastically Deformable Models. IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 19, No. 10, 1997, pp. 100-113.
- [11] Caselles, V., Kimmel, R., and Sapiro, G., Geodesic Active Contours. Int. Journal of Computer Vision, Vol. 22, 2000, pp. 61-79.
- [12] Cootes, T., Taylor, C., Cooper, D., and Graham, J., Active Shape Models - Their Training and Application. CVGIP Image Understanding, Vol. 61, No. 1, 1994, pp. 38-59.
- [13] Tomczyk, A. and Szczepaniak, P., Adaptive Potential Active Hypercontours. In: Artificial Intelligence and Soft Computing - ICAISC 2006, L. Rutkowski, R.Tadeusiewicz, L.A. Zadeh, J. Zurada (Eds.), LNAI 4029, 2006, pp. 692- 701, Springer.
- [14] Tomczyk, A., Active Hypercontours and Contextual Classification, In: 5th Int. Conference on Inteligent Systems Design and Applications (ISDA), IEEE Computer Society Press, Los Alamitos, Wroclaw, Poland, 2005, pp. 256-261.
- [15] Szczepaniak, P., Tomczyk, A., and M., P., SupervisedWeb Document Classification Using Discrete Transforms, Active Hypercontours and Expert Knowledge. WImBI 2006, LNAI 4845, Springer-Verlag, 2007, pp. 305-323.
- [16] Tomczyk, A. and Szczepaniak, P., On the Relationship between Active Contours and Contextual Classification. In: 4th International Conference on Computer Recognition Systems (CORES), Rydzyna, Poland, 2005, pp. 303- 311.
- [17] Diedrich, J., Rule Extraction from Support Vector Machines., Studies in Computional Intelligence 80, Springer-Verlag, Berlin, Heidelberg, 2008.
- [18] Craven, M. W. and Shavlik, J. W., Extracting Tree-Structured Representations of Trained Networks, NIPS’95 Proceedings of the 8th International Conference on Neural Information Processing Systems, 1995, pp. 24-30.
- [19] Andrews, R., Diedrich, J., and Tickle, A., Survey and critique of techniques for extracting rules from trained artificial neural networks. Knwoledge- Based Systems, Vol. 8, 1995, pp. 373-389.
- [20] Malone, J., McGarry, K.,Wermter, S., and Bowerman, C., Data Mining using Rule Extraction from Kohonen Self-Organising Maps. Neural Computing and Applications, Vol. 15, No. 1, 2006, pp. 9-17.
- [21] Markowska-Kaczmar, U. and Trelak, W., Fuzzy logic and evaluationary algorythm - two techniques in rule extraction from neural networks. Neurocomputing, Vol. 63, 2005, pp. 359-379.
- [22] Setino, R., Leow, W., and Zurada, J., Extraction of rules from artificial neural networks from nonlinear regression. IEEE Trans. on Neural Networks, Vol. 13, No. 3, 2002, pp. 564-577.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-50613b4e-b346-4f55-8717-02c2139a7c89