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Springer Deep Learning for Hyperspectral Image Analysis - Springer

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Description

Deep Learning for Hyperspectral Image Analysis and Classification is volume 5 in Springer's Engineering Applications of Computational Methods series, offering comprehensive coverage of advanced techniques for processing and interpreting hyperspectral imagery. This specialised text combines theoretical foundations with practical applications, bridging the gap between deep learning methodologies and remote sensing analysis. Ideal for researchers, engineers, and computer scientists working with multispectral and hyperspectral data, the book explores state-of-the-art approaches to automated image classification, feature extraction, and data interpretation. Whether you are developing machine learning models for Earth observation, medical imaging, or industrial applications, this volume provides essential insights into applying neural networks and deep learning architectures to high-dimensional spectral data. Published by Springer, a leading academic press, this engineering-focused resource equips professionals with both conceptual understanding and implementable strategies for tackling complex hyperspectral imaging challenges.

Key Features

Volume 5 in Springer's Engineering Applications of Computational Methods series, delivering advanced deep learning techniques for hyperspectral image processing.

Comprehensive coverage of deep learning architectures and neural network strategies tailored specifically for hyperspectral image analysis and automated classification tasks.

Combines theoretical frameworks with practical engineering applications, enabling professionals to implement cutting-edge methods in remote sensing and spectral data interpretation.

Addresses high-dimensional image challenges through machine learning approaches, supporting researchers across Earth observation, medical imaging, and industrial sectors.

Published by Springer, ensuring academic rigour and expert-vetted content for graduate students, researchers, and engineering professionals in computational methods.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
22 February 2022
Listed Since
26 January 2022

Barcode

No barcode data available

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