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Deep Learning for Multi-Sensor Earth Observation

Name: Deep Learning for Multi-Sensor Earth Observation
Brand: Elsevier Science
SKU: 9780443264849
Price: 148.8 EUR
Availability: InStock

Autor: Sudipan Saha

Jazyk:

Väzba: Brožovaná

Vydavateľ: Elsevier Science

Dostupnosť: U vydavateľa na objednávku

Odosielame za 28-34 dní

148.80 €

Deep Learning for Multi-Sensor Earth Observation addresses the need for transformative Deep Learning...

Informácie o knihe

Autor

Sudipan Saha

Jazyk

Angličtina

Väzba

Kniha - Brožovaná

Vydalo

2025

Stránok

350

EAN

9780443264849

ISBN

0443264848

Enbook ID

46458668

Vydavateľ

Elsevier Science

Hmotnosť

725

Rozmery

152 x 229

Kompletný popis

Deep Learning for Multi-Sensor Earth Observation addresses the need for transformative Deep Learning techniques to navigate the complexity of multi-sensor data fusion. With insights drawn from the frontiers of remote sensing technology and AI advancements, it covers the potential of fusing data of varying spatial, spectral, and temporal dimensions from both active and passive sensors. This book offers a concise, yet comprehensive, resource, addressing the challenges of data integration and uncertainty quantification from foundational concepts to advanced applications. Case studies illustrate the practicality of deep learning techniques, while cutting-edge approaches such as self-supervised learning, graph neural networks, and foundation models chart a course for future development.

Structured for clarity, the book builds upon its own concepts, leading readers through introductory explanations, sensor-specific insights, and ultimately to advanced concepts and specialized applications. By bridging the gap between theory and practice, this volume equips researchers, geoscientists, and enthusiasts with the knowledge to reshape Earth observation through the dynamic lens of deep learning.

Addresses the problem of unwieldy datasets from multi-sensor observations, applying Deep Learning to multi-sensor data integration from disparate sources with different resolution and quality
Provides a thorough foundational reference to Deep Learning applications for handling Earth Observation multi-sensor data across a variety of geosciences
Includes case studies and real-world data/examples allowing readers to better grasp how to put Deep Learning techniques and methods into practice