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Deep Learning for Hyperspectral Image Analysis and Classification

Name: Deep Learning for Hyperspectral Image Analysis and Classification
Brand: Springer Verlag, Singapore
SKU: 9789813344228
Price: 3882 CZK
Availability: InStock

Autor: Linmi Tao, Atif Mughees

Jazyk:

Vazba: Brožovaná

Vydavatel: Springer Verlag, Singapore

Dostupnost: Skladem u dodavatele

Odesíláme za 5-8 dnů

3 882 Kč

This book focuses on deep learning-based methods for hyperspectral image (HSI) analysis. Unsupervise...

Informace o knize

Autor

Linmi Tao, Atif Mughees

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2022

Stránek

207

EAN

9789813344228

Enbook ID

38637136

Vydavatel

Springer Verlag, Singapore

Hmotnost

343

Rozměry

155 x 235 x 13

Kompletní popis

This book focuses on deep learning-based methods for hyperspectral image (HSI) analysis. Unsupervised spectral-spatial adaptive band-noise factor-based formulation is devised for HSI noise detection and band categorization. The method to characterize the bands along with the noise estimation of HSIs will benefit subsequent remote sensing techniques significantly.This book develops on two fronts: On the one hand, it is aimed at domain professionals who want to have an updated overview of how hyperspectral acquisition techniques can combine with deep learning architectures to solve specific tasks in different application fields. On the other hand, the authors want to target the machine learning and computer vision experts by giving them a picture of how deep learning technologies are applied to hyperspectral data from a multidisciplinary perspective. The presence of these two viewpoints and the inclusion of application fields of remote sensing by deep learning are the original contributions of this review, which also highlights some potentialities and critical issues related to the observed development trends.