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Landsat image classification using a...

Zheng, Jian.

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Landsat image classification using a neuro-fuzzy system.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Landsat image classification using a neuro-fuzzy system./
作者:	Zheng, Jian.
面頁冊數:	37 p.
附註:	Source: Masters Abstracts International, Volume: 41-02, page: 0412.
Contained By:	Masters Abstracts International41-02.
標題:	Geography. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1410455
ISBN:	0493774270

Landsat image classification using a neuro-fuzzy system.
Zheng, Jian.

Landsat image classification using a neuro-fuzzy system. - 37 p.

Source: Masters Abstracts International, Volume: 41-02, page: 0412.

Thesis (M.A.)--San Jose State University, 2002.

This study investigates an alternative classification algorithm, NEFCLASS, and its ability to classify remote sensing images. NEFCLASS is a Neuro-fuzzy System that is capable of generating a set of linguistic rules. These rules allow the user to check and interpret the classification results. This study also shows that the neural net rules stabilized after only a few training iterations. The land-use/land-cover classification result produced by NEFCLASS is compared to the result produced by a conventional classification algorithm, Maximum Likelihood Classifier (MLC). NEFCLASS produced better classification accuracy than MLC.

ISBN: 0493774270Subjects--Topical Terms:

524010
Geography.

Landsat image classification using a neuro-fuzzy system.
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520 $a This study investigates an alternative classification algorithm, NEFCLASS, and its ability to classify remote sensing images. NEFCLASS is a Neuro-fuzzy System that is capable of generating a set of linguistic rules. These rules allow the user to check and interpret the classification results. This study also shows that the neural net rules stabilized after only a few training iterations. The land-use/land-cover classification result produced by NEFCLASS is compared to the result produced by a conventional classification algorithm, Maximum Likelihood Classifier (MLC). NEFCLASS produced better classification accuracy than MLC.
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