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dc.contributor.author葉志聖en_US
dc.contributor.authorJyh-Shenq Yehen_US
dc.contributor.author史天元en_US
dc.contributor.authorTian-Yuan Shihen_US
dc.date.accessioned2014-12-12T02:13:04Z-
dc.date.available2014-12-12T02:13:04Z-
dc.date.issued1994en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#NT830015043en_US
dc.identifier.urihttp://hdl.handle.net/11536/58736-
dc.description.abstract本研究探討一種結合光譜資訊和空間資訊的分類法,稱為AMOEBA,並與 ISOCLASS、K-means等常用的群聚法做比較,以期瞭解加入空間資訊後, 影像分類的情形。另外也探討AMOEBA、ISOCLASS、K-means等群聚法,所 需的參數與參數設定的難易程度。 This study investigates a clustering method which incooperates both spectral and spatial information, named AMOEBA. The cation results are compared with ISODATA and K-means. The setting issues of the parameters for AMOEBA, ISODATA and K- means are also addressed.zh_TW
dc.language.isozh_TWen_US
dc.subject...en_US
dc.titleAMOEBA影像分類技術之研究zh_TW
dc.titleA Study on the AMOEBA Image Classification Schemeen_US
dc.typeThesisen_US
dc.contributor.department土木工程學系zh_TW
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