抄録
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.
本文言語 | English |
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ページ | II-1063 - II-1068 |
出版ステータス | Published - 1999 12月 1 |
外部発表 | はい |
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 22 → 1999 8月 25 |
Other
Other | Proceedings of the 1999 IEEE International Fuzzy Systems Conference, FUZZ-IEEE'99 |
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City | Seoul, South Korea |
Period | 99/8/22 → 99/8/25 |
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