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The application of artificial neural networks to the analysis of remotely sensed data / J.F. Mas in International Journal of Remote Sensing IJRS, vol 29 n°3-4 (February 2008)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 29 n°3-4 (February 2008) . - pp 617 - 663 Titre : The application of artificial neural networks to the analysis of remotely sensed data Type de document : Article/Communication Auteurs : J.F. Mas, Auteur ; J.J. Flores, Auteur Année de publication : 2008 Article en page(s) : pp 617 - 663 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] apprentissage automatique [Termes IGN] classification par réseau neuronal [Termes IGN] image aérienne [Termes IGN] image satellite [Termes IGN] réseau neuronal artificiel Résumé : (Auteur) Artificial neural networks (ANNs) have become a popular tool in the analysis of remotely sensed data. Although significant progress has been made in image classification based upon neural networks, a number of issues remain to be resolved. This paper reviews remotely sensed data analysis with neural networks. First, we present an overview of the main concepts underlying ANNs, including the main architectures and learning algorithms. Then, the main tasks that involve ANNs in remote sensing are described. The limitations and crucial issues relating to the application of the neural network approach are discussed. A brief review of the implementation of ANNs in some of the most popular image processing software packages is presented. Finally, we discuss the application perspectives of neural networks in remote sensing image analysis. Copyright Taylor & Francis Numéro de notice : A2008-004 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160701352154 En ligne : https://doi.org/10.1080/01431160701352154 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28999 [article]

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