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Computational intelligence based hyp...

Bajaj, Anu.

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Computational intelligence based hyperspectral image processing.. Volume 1

Record Type:	Electronic resources : Monograph/item
Title/Author:	Computational intelligence based hyperspectral image processing./ edited by Anu Bajaj, Ajith Abraham.
other author:	Bajaj, Anu.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	x, 218 p. :ill. (chiefly color), digital ;24 cm.
[NT 15003449]:	Unveiling Hyperspectral and Multispectral Image Processing: A Contemporary Exploration of Band Selection, Dimensionality Reduction, and Compressive Sensing Techniques -- Hyperspectral Image Registration: State-of-the-Art and Future Challenges -- Hardware Accelerators for Hyperspectral Image Classification in Space: A Survey on Deep Learning based Architectures for Hardware Accelerators.
Contained By:	Springer Nature eBook
Subject:	Hyperspectral imaging. -
Online resource:	https://doi.org/10.1007/978-3-031-83123-2
ISBN:	9783031831232

Computational intelligence based hyperspectral image processing.. Volume 1
Computational intelligence based hyperspectral image processing.Volume 1[electronic resource] /edited by Anu Bajaj, Ajith Abraham. - Cham :Springer Nature Switzerland :2025. - x, 218 p. :ill. (chiefly color), digital ;24 cm. - Intelligent systems reference library,v. 2681868-4408 ;. - Intelligent systems reference library ;v. 268..

Unveiling Hyperspectral and Multispectral Image Processing: A Contemporary Exploration of Band Selection, Dimensionality Reduction, and Compressive Sensing Techniques -- Hyperspectral Image Registration: State-of-the-Art and Future Challenges -- Hardware Accelerators for Hyperspectral Image Classification in Space: A Survey on Deep Learning based Architectures for Hardware Accelerators.

Hyperspectral imaging has revolutionized fields ranging from environmental monitoring to medical diagnostics by providing detailed spectral information across vast datasets. However, the complexity and high dimensionality of hyperspectral data pose significant challenges in analysis and interpretation. "Computational Intelligence based Hyperspectral Image Processing" is a comprehensive guide to overcoming these challenges by leveraging the latest computational intelligence techniques. This Volume comprises of 9 chapters that illustrate how computational intelligence-based solutions has been successful to improve efficiency and productivity, quality control, and in enhancing innovation and competitiveness with cost reduction. This book is an essential resource for researchers, professionals, and students working in remote sensing, image processing, and computational intelligence. Whether you're new to the field or looking to deepen your expertise, this book provides the tools and knowledge you need to succeed in the fast-evolving world of hyperspectral imaging.

ISBN: 9783031831232

Standard No.: 10.1007/978-3-031-83123-2doiSubjects--Topical Terms:

3711381
Hyperspectral imaging.

LC Class. No.: TR267.73

Dewey Class. No.: 621.367

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520 $a Hyperspectral imaging has revolutionized fields ranging from environmental monitoring to medical diagnostics by providing detailed spectral information across vast datasets. However, the complexity and high dimensionality of hyperspectral data pose significant challenges in analysis and interpretation. "Computational Intelligence based Hyperspectral Image Processing" is a comprehensive guide to overcoming these challenges by leveraging the latest computational intelligence techniques. This Volume comprises of 9 chapters that illustrate how computational intelligence-based solutions has been successful to improve efficiency and productivity, quality control, and in enhancing innovation and competitiveness with cost reduction. This book is an essential resource for researchers, professionals, and students working in remote sensing, image processing, and computational intelligence. Whether you're new to the field or looking to deepen your expertise, this book provides the tools and knowledge you need to succeed in the fast-evolving world of hyperspectral imaging.
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