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dc.contributor.authorHuang, Kou-Yuanen_US
dc.contributor.authorChou, Ying-Liangen_US
dc.date.accessioned2014-12-08T15:04:19Z-
dc.date.available2014-12-08T15:04:19Z-
dc.date.issued2008en_US
dc.identifier.isbn978-1-4244-1820-6en_US
dc.identifier.issn1098-7576en_US
dc.identifier.urihttp://hdl.handle.net/11536/2830-
dc.description.abstractA Hierarchical system is proposed by using simulated annealing for the detection of fines, circles, ellipses, and hyperbolas in image. The hierarchical detection procedures re type by type and pattern by pattern. The equation of ellipse and hyperbola is defined under translation and rotation. distance from all points to all patterns is defined as the error. Also we use the minimum error to determine the number of patterns. The proposed simulated annealing parameter detection system can search a set of parameter vectors for the global minimal error. In the experiments, using the hierarchical system, the result of the detection of a large number of simulated image patterns is better than that of using the synchronous system. In the seismic experiments, both of two systems can well detect line of direct wave and hyperbola of reflection wave in the simulated one-shot seismogram and the real seismic data, but the hierarchical system can converge faster. The results of seismic pattern detection can improve seismic interpretation and further seismic data processing.en_US
dc.language.isoen_USen_US
dc.titleSimulated Annealing for Hierarchical Pattern Detection and Seismic Applicationsen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2008 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-8en_US
dc.citation.spage1257en_US
dc.citation.epage1264en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000263827200203-
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