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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: 937.64 RON
Availability: InStock

Autor: Linmi Tao, Atif Mughees

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Legare: Carte broșată

Editura: Springer Verlag, Singapore

Disponibilitate: În depozitul extern

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

Informații despre carte

Autor

Linmi Tao, Atif Mughees

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2022

Pagini

207

EAN

9789813344228

Enbook ID

38637136

Editura

Springer Verlag, Singapore

Greutate

343

Dimensiuni

155 x 235 x 13

Descriere completă

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.