Neuro-fuzzy classifier for land cover classification

Sang Gu Lee*, Jong Gyu Han, Kwang Hoon Chi, Jae Young Suh, Hee Hyol Lee, Michio Miyazaki, Kageo Akizuki


研究成果: Paper査読

13 被引用数 (Scopus)


In this paper, we present a neuro-fuzzy classifier derived from the generic model of a 3-layer fuzzy perceptron and implement a classification software system for land cover classification. Comparisons with the proposed and maximum-likelihood classifiers are also presented. We use the image of Daeduk Science Complex Town which is obtained by AMS (Airborne Multispectral Scanner). The results show that the mixed composition areas such as 'bare soil', 'dried grass' and 'coniferous tree' are classified more accurately in the proposed method. This system can be used to classify the mixed composition area like the natural environment of the Korean peninsula. This classifier is superior in suppression of the classification errors for mixtures of land cover signatures.

ページII-1063 - II-1068
出版ステータスPublished - 1999 12月 1
イベントProceedings of the 1999 IEEE International Fuzzy Systems Conference, FUZZ-IEEE'99 - Seoul, South Korea
継続期間: 1999 8月 221999 8月 25


OtherProceedings of the 1999 IEEE International Fuzzy Systems Conference, FUZZ-IEEE'99
CitySeoul, South Korea

ASJC Scopus subject areas

  • ソフトウェア
  • 理論的コンピュータサイエンス
  • 人工知能
  • 応用数学


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