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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Autors principals:	Saeid Amini, Saeid Homayouni, Abdolreza Safari, Ali A. Darvishsefat
Format:	Artigo
Idioma:	Inglês
Publicat:	Taylor & Francis Group 2018-04-01
Col·lecció:	Geo-spatial Information Science
Matèries:	Object-based classification Random Forest algorithm multi-resolution segmentation (MRS) hyperspectral imagery
Accés en línia:	http://dx.doi.org/10.1080/10095020.2017.1399674
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