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Publications

  • Bücker, Szepannek, Weihs (2010): Local Classification of Discrete Variables by Latent Class Models, in: H.Locarek-Junge, C.Weihs (eds): Classification as a Tool for Research, Springer, S. 126 - 135.
  • Müller, Schiffner, Schwender, Szepannek, Weihs, Ickstadt (2010): Local Analysis of SNP Data, in: H.Locarek-Junge, C.Weihs (eds): Classification as a Tool for Research, Springer, S. 473 - 480.
  • Szepannek, Gruhne, Bischl, Krey, Harczos, Klefenz, Dittmar, Weihs (2010): Perceptually Based Phoneme Recognition in Popular Music, in: H.Locarek-Junge, C.Weihs (eds): Classification as a Tool for Research, Springer, S. 751 - 758.
  • Weihs, Szepannek (2009): Distances in Classification, Transactions on Case-based Reasoning, Vol. 2, No. 1, S. 3–14.
  • Szepannek, Harczos, Klefenz, Weihs (2009): Extending Features for Automatic Speech Recognition by Means of Auditory Modelling, in: Proc. of the. European Signal Processing Conference (EUSIPCO), Glasgow, S. 1235 - 1239.
  • Szepannek, Harczos, Klefenz, Weihs (2009): Extending Features for Automatic Speech Recognition by Means of Auditory Modelling, Proc. EUSIPCO 2009 (akzeptiert).
  • Harczos, Werner, Szepannek, Brandenburg (2009): Evaluation of Cues for Horizontal-Plane Localization with Bilateral Cochlear Implants, in: Proc. Int. Symposium on Auditory and Audiological Research ISAAR, Helsingør, Denmark, 2009 (26.8-28.8, akzeptiert).
  • Szepannek, Harczos, Klefenz, Weihs (2009): Combining Different Auditory Model Based Feature Extraction Principles for Feature Enrichment in Automatic Speech Recognition, in: A. Karpov (ed.): Specom 2009 Proceedings ISBN 978-5-8088-0442-5, S. 205-210.
  • Schiffner, Szepannek, Monthé, Weihs (2009): Localized Logistic Regression for Categorical Influential Factors, in A. Fink, B. Lausen, W. Seidel, and A. Ultsch (eds.): Advances in Data Analysis, Data Handling and Business Intelligence, Springer, S. 185-195.
  • Harczos, Werner, Szepannek (2008): Formant Map Counterpart in Auditory Processing Based on Cochlear Pressure Wave Trajectories, Proc. IEEE BioCAS 2008, S. 45-48.
  • Szepannek (2008): Post Cochlea Processing - Informationsextraktion aus simulierten Aktionspotenzialen des Hörnervs, Dissertation.
  • Szepannek, Bischl, Weihs (2008): On the Combination of Locally Optimal Pairwise Classifiers, Journal of Engineering Applications of Artificial Intelligence, 22 (1), S. 79-85.
  • Szepannek, Schiffner, Wilson, Weihs (2008): Local Modelling in Classification. in P.Perner (eds): Advances in Data Mining, Springer LNAI 5077, 153-164.
  • Szepannek (2008): Different Subspace Classification - Verfahren zur Datenanalyse, -interpretation, -visualisierung und Vorhersage in hochdimensionalen Räumen, vdm, Saarbrücken.
  • Harczos, Szepannek, Klefenz (2007): Towards Automatic Speech Recognition Based on Cochlear Travelling Wave Delay Trajectories. Proc. ISAAR Conference, Helsingoer.
  • Szepannek, Bischl, Weihs (2007): On the Combination of Locally Optimal Pairwise Classifiers. in P. Perner (Ed.) Machine Learning and Data Mining in Pattern Recognition, Springer LNAI 4571, 104-116.
  • Harczos, Nogueira, Szepannek, Klefenz (2007): Comparative Evaluation of Successive Cochlear Modelling Stages as Possible Front-Ends for Automatic Speech Recognition. Proc. International Congress on Acoustics, Madrid.
  • Harczos, Szepannek, Katai, Klefenz (2006): An Auditory Model Based Vowel Classification. Proc. IEEE Biomedical Circuits & Systems Conference 2006, London, S. 69-72.
  • Szepannek, Harczos, Klefenz, Katai, Schikowski, Weihs (2006): Vowel Classification by a Perceptually Motivated Neurophysiologically Parameterized Auditory Model. in: R. Deckert, H. Lenz, W. Gaul (eds): Advances in Data Analysis, Springer, Heidelberg, 653-660.
  • Szepannek, Weihs (2006): Local Modelling in Classification on Different Feature Subspaces. in P.Perner (eds): Advances in Data Mining, LNAI 4065, 226-238.
  • Weihs, Szepannek, Ligges, Luebke, Raabe (2006): Local Models in Register Classification by Timbre. in V.Batagelij, H.Bock, A.Ferligoj and A.Ziberna (eds): Data Science and Classification, Springer-Verlag, Heidelberg, 315-322.
  • Szepannek, Weihs (2006): Variable Selection for Discrimination of More Than Two Classes Where Data are Sparse. in: M.Spiliopoulou, R.Kruse, A.Nürnberger, C.Borgelt, W.Gaul (eds.): From Data and Information Analysis to Knowledge Engineering, Springer-Verlag, Heidelberg, 700-707.
  • Szepannek, Klefenz, Weihs (2005): Schallanalyse: Neuronale Repräsentation des Hörvorgangs als Basis, Informatikspektrum 28, 5/2005, 389-395.
  • Szepannek, Luebke, Weihs (2005): Understanding Patterns with Different Subspace Classification , in P. Perner and A. Imiya (eds.): Machine Learning and Data Mining (MLDM), Springer Lecture Notes in Artificial Intelligence (LNAI), Volume 3587, 110-119.
  • Röver, Szepannek (2005): Application of a Genetic algorithm to Variable Selection in Fuzzy Clustering, in: C.Weihs, W.Gaul (eds.): Classification - The Ubiquitous Challenge, Springer-Verlag, Heidelberg, 674-681.
  • Szepannek, Luebke (2005): Different Subspace Classification, in: C.Weihs, W.Gaul (eds.): Classification - The Ubiquitous Challenge, Springer-Verlag, Heidelberg, 224-231.

 

Technical Reports und Forschungsberichte

  • Breiter, Wornowitzki, Schaltenbrand, Priefer, Bischl, Szepannek (2009): Data Mining Cup 2009 – Vorhersage von Buchabverkäufen, Forschungsbericht 02/2009, Fakultät Statistik, TU Dortmund.
  • Szepannek, Weihs (2006): Explorative Development of Information Extraction Schemes for Speech Recognition from Simulated Auditory Neural Response Data via Parallel Local Hubel-Wiesel Networks, Forschungsbericht 02/2006, Fachbereich Statistik, Universität Dortmund
  • Wolfrum, Gepperth, Sandamirskaya, Webber, Raabe, Szepannek, Schoener (2006): Modelling and Understanding of Chatter. Technical Report 22/06, SFB 475, Universität Dortmund.
  • Szepannek, Raabe, Webber, Weihs (2006): Prediction of Spiralling in BTA Deep-hole Drilling -- Estimating the System's Eigenfrequencies. Technical Report 19/06, SFB 475, Universität Dortmund.
  • Szepannek, Weihs (2006): Local Modelling in Classification on Different Feature Subspaces. Technical Report 08/2006, SFB 475, Universität Dortmund.
  • Szepannek, Ligges, Luebke, Raabe, Weihs (2005): Local Models in Register Classification by Timbre. Technical Report 47/2005, SFB 475, Universität Dortmund.
  • Szepannek, Weihs (2005): Variable Selection for Discrimination of More Than Two Classes Where Data are Sparse. Technical Report 40/2005, SFB 475, Universität Dortmund.
  • Szepannek, Luebke (2004): Different Subspace Classification, Technical Report 69/2004, SFB 475, Universität Dortmund.
  • Röver, Szepannek (2004): Application of a Genetic algorithm to Variable Selection in Fuzzy Clustering, Technical Report 76/2004, SFB 475, Universität Dortmund.
  • Szepannek, Luebke, Weihs (2003): Gruppierung der Spielweise von Vereinen in der Fußballbundesligasaison 2002/03 mit Hilfe von Clusteranalysen, Forschungsbericht 04/2003, Fachbereich Statistik, Universität Dortmund