Price loading...

Deep Learning for Multi-Sensor Earth Observation

Management

Price data last checked 104 day(s) ago - refreshing...

View at Amazon

Price History & Forecast

No Price Data Available

Price history will appear here once data is collected from Amazon.

Price Distribution

No price data available for histogram

Description

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

Product Specifications

Format: paperback
ASIN: 0443264848
Category: Books > Subjects > Business, Finance & Law > Management
Domain: Amazon UK
Release Date: 09 February 2025
Listed Since: 28 August 2024

Barcode

No barcode data available

Deep Learning for Multi-Sensor Earth Observation

Price History & Forecast

No Price Data Available

Price Distribution

Description

Product Specifications

Barcode

Similar Products You Might Like

Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science and Geosciences

Advances in Machine Learning and Image Analysis for GeoAI

Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing

Earth Observation Data Analytics Using Machine and Deep Learning: Modern tools, applications and challenges (Computing and Networks)

Elsevier Remote Sensing of Soil and Land Surface Processes Book

Artificial Intelligence for Subsurface Characterization and Monitoring

Deep Learning for Remote Sensing Images with Open Source Software (Signal and Image Processing of Earth Observations)

Sensitivity Analysis in Earth Observation Modelling

Earth Observation Applications to Landslide Mapping, Monitoring and Modeling: Cutting-edge Approaches with Artificial Intelligence, Aerial and Satellite Imagery

Data Analytics and Artificial Intelligence for Earth Resource Management

Artificial Intelligence in Earth Science: Best Practices and Fundamental Challenges

Multi-sensor Fusion for Autonomous Driving

Multi-Sensor and Multi-Temporal Remote Sensing: Specific Single Class Mapping

Deep Learning Models: A Practical Approach for Hands-On Professionals (Transactions on Computer Systems and Networks)

Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches: Theory and Practical Applications

Fundamentals and Methods of Machine and Deep Learning: Algorithms, Tools, and Applications

Large-Scale Machine Learning in the Earth Sciences - CRC Press

An Introduction to Approaches and Modern Applications with Ensemble Learning (Computer Science, Technology and Applications)

Advances in Subsurface Data Analytics: Traditional and Physics-Based Machine Learning

Computers in Earth and Environmental Sciences: Artificial Intelligence and Advanced Technologies in Hazards and Risk Management

Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions

Deep Learning for Sustainable Agriculture (Cognitive Data Science in Sustainable Computing)

Elsevier Machine Learning for Planetary Science - Research Guide

Earth Observation in Urban Monitoring: Techniques and Challenges