Object-based classification of hyperspectral data using Random Forest algorithm
This paper presents a new framework for object-based classification of high-resolution hyperspectral data. This multi-step framework is based on multi-resolution segmentation (MRS) and Random Forest classifier (RFC) algorithms. The first step is to determine of weights of the input features while us...
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| 主要な著者: | , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Taylor & Francis Group
2018-04-01
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| シリーズ: | Geo-spatial Information Science |
| 主題: | |
| オンライン･アクセス: | http://dx.doi.org/10.1080/10095020.2017.1399674 |
| タグ: |
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