Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Tasks and Methods in Applied Artificial Intelligence - 11 th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA-1998-AIE, Proceedings |
| Herausgeber/-innen | Moonis Ali, Angel Pasqual del Pobil, Jose Mira |
| Seiten | 437-447 |
| Seitenumfang | 11 |
| Publikationsstatus | Veröffentlicht - 1998 |
| Veranstaltung | 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA-1998-AIE - Benicassim, Spanien Dauer: 1 Juni 1998 → 4 Juni 1998 |
Publikationsreihe
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Band | 1416 |
| ISSN (Print) | 0302-9743 |
| ISSN (elektronisch) | 1611-3349 |
Abstract
SOLUTION is a knowledge based system, which can be used to automatically configure and adapt the low level part of image processing systems with respect to different tasks and input images. The task specification contains a characterization of the properties of the class of input images to be processed, a description of the relevant properties of the output image to be expected, requests about some general properties of the algorithms to be used, and a test image. In the configuration phase appropriate operators are selected and processing paths are assembled. In a subsequent adaptation phase the free parameters of the selected processing paths are adapted such that the specified properties of the output image are approximated as close as possible. All task specifications including the specification of the requested image properties are given in natural spoken terms like the Thickness or Parallelism of contours. The adaptation is rule based and the knowledge needed therefore can be learned automatically using a combination of different learning paradigms. This paper describes the adaptation and the learning part of SOLUTION.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Theoretische Informatik
- Informatik (insg.)
- Allgemeine Computerwissenschaft
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Tasks and Methods in Applied Artificial Intelligence - 11 th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA-1998-AIE, Proceedings. Hrsg. / Moonis Ali; Angel Pasqual del Pobil; Jose Mira. 1998. S. 437-447 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 1416).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - SOLUTION for a learning configuration system for image processing
AU - Liedtke, C. E.
AU - Münkel, H.
AU - Rost, U.
N1 - Publisher Copyright: © Springer-Verlag Berlin Heidelberg 1998.
PY - 1998
Y1 - 1998
N2 - SOLUTION is a knowledge based system, which can be used to automatically configure and adapt the low level part of image processing systems with respect to different tasks and input images. The task specification contains a characterization of the properties of the class of input images to be processed, a description of the relevant properties of the output image to be expected, requests about some general properties of the algorithms to be used, and a test image. In the configuration phase appropriate operators are selected and processing paths are assembled. In a subsequent adaptation phase the free parameters of the selected processing paths are adapted such that the specified properties of the output image are approximated as close as possible. All task specifications including the specification of the requested image properties are given in natural spoken terms like the Thickness or Parallelism of contours. The adaptation is rule based and the knowledge needed therefore can be learned automatically using a combination of different learning paradigms. This paper describes the adaptation and the learning part of SOLUTION.
AB - SOLUTION is a knowledge based system, which can be used to automatically configure and adapt the low level part of image processing systems with respect to different tasks and input images. The task specification contains a characterization of the properties of the class of input images to be processed, a description of the relevant properties of the output image to be expected, requests about some general properties of the algorithms to be used, and a test image. In the configuration phase appropriate operators are selected and processing paths are assembled. In a subsequent adaptation phase the free parameters of the selected processing paths are adapted such that the specified properties of the output image are approximated as close as possible. All task specifications including the specification of the requested image properties are given in natural spoken terms like the Thickness or Parallelism of contours. The adaptation is rule based and the knowledge needed therefore can be learned automatically using a combination of different learning paradigms. This paper describes the adaptation and the learning part of SOLUTION.
UR - http://www.scopus.com/inward/record.url?scp=84958087884&partnerID=8YFLogxK
U2 - 10.1007/3-540-64574-8_429
DO - 10.1007/3-540-64574-8_429
M3 - Conference contribution
AN - SCOPUS:84958087884
SN - 3540645748
SN - 9783540645740
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 437
EP - 447
BT - Tasks and Methods in Applied Artificial Intelligence - 11 th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA-1998-AIE, Proceedings
A2 - Ali, Moonis
A2 - del Pobil, Angel Pasqual
A2 - Mira, Jose
T2 - 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA-1998-AIE
Y2 - 1 June 1998 through 4 June 1998
ER -