Ontology type: schema:Chapter Open Access: True
2001-08-28
AUTHORS ABSTRACTFeature extraction and knowledge discovery from a large amount of image data such as remote sensing images have become highly required recent years. In this study, a framework for data mining from a set of time-series images including moving objects was presented. Time-series images are transformed into time-series cluster addresses by using clustering by two-stage SOM (Self-organizing map) and time-dependent association rules were extracted from it. Semantically indexed data and extracted rules are stored in the object-relational database, which allows high-level queries by entering SQL through the user interface. This method was applied to weather satellite cloud images taken by GMS-5 and its usefulness was evaluated. More... »
PAGES204-215
Principles of Data Mining and Knowledge Discovery
ISBN
978-3-540-42534-2
978-3-540-44794-8
http://scigraph.springernature.com/pub.10.1007/3-540-44794-6_17
DOIhttp://dx.doi.org/10.1007/3-540-44794-6_17
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