Catalogue en ligne IGN

Learning to Understand Remote Sensing Images, 1. Volume 1 / Qi Wang (2019)

Public

contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre de série :	Learning to Understand Remote Sensing Images, 1
Titre :	Volume 1
Type de document :	Monographie
Auteurs :	Qi Wang, Editeur scientifique
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2019
Importance :	426 p.
ISBN/ISSN/EAN :	978-3-03897-685-1
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Traitement d'image mixte [Termes descripteurs IGN] analyse texturale [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] apprentissage semi-dirigé [Termes descripteurs IGN] fusion d'images [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] image Landsat [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] réseau neuronal convolutif
Résumé :	(Editeur) With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.
Numéro de notice :	26301A
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE/INFORMATIQUE
Nature :	Monographie
DOI :	10.3390/books978-3-03897-685-1
date de publication en ligne :	09/12/2019
En ligne :	https://doi.org/10.3390/books978-3-03897-685-1
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95033

Voir aussi

Learning to Understand Remote Sensing Images, 2. Volume 2 / Qi Wang (2019)

Public

contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre de série :	Learning to Understand Remote Sensing Images, 2
Titre :	Volume 2
Type de document :	Monographie
Auteurs :	Qi Wang, Editeur scientifique
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2019
Importance :	376 p.
ISBN/ISSN/EAN :	978-3-03897-699-8
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Traitement d'image mixte [Termes descripteurs IGN] analyse texturale [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] apprentissage semi-dirigé [Termes descripteurs IGN] fusion d'images [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] image Landsat [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] réseau neuronal convolutif
Résumé :	(Editeur) With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.
Numéro de notice :	26301B
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE/INFORMATIQUE
Nature :	Monographie
DOI :	10.3390/books978-3-03897-699-8
date de publication en ligne :	09/12/2019
En ligne :	https://doi.org/10.3390/books978-3-03897-699-8
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95034

Voir aussi

IGN

Centre dedocumentation
scientifique

Accueil

Sélection de la langue

Adresse

Se connecter

Actualité

L'actu-47

Agenda

Informations pratiques

IGN / ENSG

L'IGN a pour vocation

Accès directs

2014 IGN

IGN

Centre dedocumentationscientifique

Accueil

Sélection de la langue

Adresse

Se connecter

Actualité

L'actu-47

Agenda

Informations pratiques

IGN / ENSG

L'IGN a pour vocation

Accès directs

2014 IGN

Centre dedocumentation
scientifique