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Signature verification using self-organizing feature map

MAUTNER, P., MATOUŠEK, V., ROHLÍK, O., KEMPF, J. Signature verification using self-organizing feature map. In CIRAS 2003. Singapore: National University of Singapore, 2003. s. 1-4.
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In this paper we describe the use of the SOFM neural network model for signature verification. The biometric data of all signatures were acquired by a special digital data acquisition pen and fast wavelet transformation was used forfeature extraction. The part of authentic signature data was used for training the SOFM signature verifer. The architecture of the verifer and achieved results are discussed here and ideas for future research are also suggested.

Novel communication concepts for municipal information services

EKŠTEIN, K., HITZENBERGER, L., KLEČKOVÁ, J., KRUTIŠOVÁ, J., KUBIŠTA, J., MATOUŠEK, V., MOUČEK, R., TAUŠER, K. Novel communication concepts for municipal information services. In SoftCOM 2003. Split: Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture University of Split, 2003. s. 705-709. ISBN: 953-6114-64-X
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In this paper we report on some problems arising during the building of a bilingual dialogue system, concerning especially robust speech recognition method, linguistic analysis of incomplete utterances and their sementic interpretation, dialogue modelling and dialogue control, system response generation, as well as a unique knowledge based technique of automated generation of a corpus of training sentences.

Hybrid analytic/ANN-based acoustic-phonetic decoding

EKŠTEIN, K., MATOUŠEK, V., MOUČEK, R. Hybrid analytic/ANN-based acoustic-phonetic decoding. In Elektronische Sprachsignalverarbeitung. Dresden: Universitätsverlag & Buchhandel, 2003. s. 14-21. ISBN: 3-935712-83-9
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The presented article introduces an alternative acoustic-phonetic decoding scheme based on hybrid configuration of multilayer perceptron (MLP) neural network and knowledge-based analytic speech signal survey module.

Comparison of signature verification methods for data acquisition pen

MAUTNER, P., ROHLÍK, O., MATOUŠEK, V., KEMPF, J., SCHARFENBERG, G. Comparison of signature verification methods for data acquisition pen . In 48. Internationales Wissenschaftliches Kolloquium. Ilmenau: Technische Universität Ilmenau, 2003. s. 147-148.
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There are many commercial systems designed for person indentification worldwide. Among the most popular rank those based on fingerprints, ID cards and signature verification. The current systems are based on input devices that consist of at least two parts. The obvious problem of such an approach is the limited mobility of a system composed of several parts. To avoid disadvantages of current on-line data acquisition systems mentioned above we have constructed a nigue pen that integrates all the electronic devices needed for data acěuisition inside the pen. The paper reports our experience with the signature verification methods developed to process the signals produced by the pen.

Hybrid method of feature extraction from biometric signals

MATOUŠEK, V., MAUTNER, P., MUSIL, M., ROHLÍK, O. Hybrid method of feature extraction from biometric signals. In 48. Internationales Wissenschaftliches Kolloquium. Ilmenau: Technische Universität Ilmenau, 2003. s. 127-128.
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The article describes a hybrid approach to the feature extraction from signals generated by the special biometric pen with which the high recognition rates were achieved. The method is based on the combination of structural and statistic approaches; it computes the feature values as coefficients of the transformation of predefined wave shopes to the signal wave. The developed feature extraction method achieves much better recognition rates as all still developed techniques.

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