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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: 179.02 EUR
Availability: InStock

Автор: Linmi Tao, Atif Mughees

Език:

Корици: С меки корици

Издател: Springer Verlag, Singapore

Наличност: Външен склад

Изпращаме след 5-8 дни

179.02 € 350.14 лв

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

Информация за книгата

Автор

Linmi Tao, Atif Mughees

Език

Английски език

Корици

Книга - С меки корици

Издадена

2022

страници

207

EAN

9789813344228

Enbook ID

38637136

Издател

Springer Verlag, Singapore

Теглоt

343

Размери

155 x 235 x 13

Пълно описание

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.