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Elsevier Deep Learning for Multi-Sensor Earth Observation

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Description

Deep Learning for Multi-Sensor Earth Observation by Elsevier provides a technical resource for navigating the complexities of multi-sensor data fusion. This book examines how to integrate data from both active and passive sensors, addressing the challenges of varying spatial, spectral, and temporal dimensions. Readers gain insights into the frontiers of remote sensing technology and AI advancements. The text covers foundational concepts through to advanced applications, focusing on data integration and uncertainty quantification. Through specific case studies, the book demonstrates how transformative Deep Learning techniques can be applied to handle complex remote sensing datasets effectively.

Key Features

This Elsevier publication covers the integration of data from active and passive sensors for improved remote sensing results.

The text addresses the technical challenges of fusing data with different spatial, spectral, and temporal dimensions.

Readers can explore advanced applications of Deep Learning techniques specifically designed for multi-sensor Earth observation.

The book provides guidance on uncertainty quantification and data integration from foundational concepts to advanced levels.

Case studies are included to demonstrate practical applications of AI advancements in the field of remote sensing.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
09 February 2025
Listed Since
28 August 2024

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