Search

Your search keyword '"Lubbe, J. C. A."' showing total 8 results
Start Over Author "Lubbe, J. C. A." Publication Type Books Publication Type eBooks
8 results on '"Lubbe, J. C. A."'

1. Paper Retrieval Based on Specific Paper Features: Chain and Laid Lines

Author

van Staalduinen, M., van der Lubbe, J. C. A., Backer, E., Paclík, P., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Gunsel, Bilge, editor, Jain, Anil K., editor, Tekalp, A. Murat, editor, and Sankur, Bülent, editor

Published
2006
Full Text
View/download PDF

4. KEYMEX: An expert system for the design of key management schemes

Author

van der Lubbe, J. C. A., Boekee, D. E., Goos, G., editor, Hartmanis, J., editor, Barstow, D., editor, Brauer, W., editor, Brinch Hansen, P., editor, Gries, D., editor, Luckham, D., editor, Moler, C., editor, Pnueli, A., editor, Seegmüller, G., editor, Stoer, J., editor, Wirth, N., editor, Seberry, Jennifer, editor, and Pieprzyk, Josef, editor

Published
1990
Full Text
View/download PDF

7. Paper Retrieval Based on Specific Paper Features: Chain and Laid Lines.

Author

Gunsel, Bilge, Jain, Anil K., Tekalp, A. Murat, Sankur, Bülent, Staalduinen, M., Lubbe, J. C. A., Backer, E., and Paclík, P.

Abstract

This paper presents paper retrieval using the specific paper features chain and laid lines. Paper features are detected in digitized paper images and they are represented such that they could be used for retrieval. Optimal retrieval performance is achieved by means of a trainable similarity measure for a given set of paper features. By means of these methods a retrieval system is developed that art experts could use real-time in order to speed up their paper research. [ABSTRACT FROM AUTHOR]

Published
2006
Full Text
View/download PDF

8. A modulated Parzen-windows approach for probability density estimation.

Author

Goos, Gerhard, Hartmanis, Juris, Leeuwen, Jan, Xiaohui Liu, Cohen, Paul, Berthold, Michael, Eijkel, G. C., Lubbe, J. C. A., and Backer, E.

Abstract

The Parzen-window approach is a well-known technique for estimating probability density functions. This paper introduces a modulated Parzen-windows approach. This approach uses kernels at equidistant samples to obtain a probability density function more efficiently. Experiments on both artificial and real data show that the modulated Parzen-windows approach is more efficient in probability density function estimation, without costly preprocessing or severe loss of accuracy. [ABSTRACT FROM AUTHOR]

Published
1997
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results