Artículos relacionados a Deep Learning for Multi-Sensor Earth Observation

Deep Learning for Multi-Sensor Earth Observation - Tapa blanda

 
9780443264849: Deep Learning for Multi-Sensor Earth Observation
Tapa blanda
ISBN 10: 0443264848 ISBN 13: 9780443264849
Editorial: Elsevier - Health Sciences Division, 2025

Sinopsis

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.

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Acerca del autor

Sudipan Saha is currently an Assistant Professor at Yardi School of Artificial Intelligence, Indian Institute of Technology (IIT) Delhi, New Delhi, India. Previously, he worked as a postdoctoral researcher at the Artificial Intelligence for Earth Observation (AI4EO) Lab, Technical University of Munich, Germany (2020-2022). He received a Ph.D. degree in Information and Communication Technologies from the University of Trento and Fondazione Bruno Kessler (FBK), Trento, Italy in 2020, working with Dr. Francesca Bovolo and Prof. Lorenzo Bruzzone. He is the recipient of FBK Best Student Award 2020. Previously, he obtained the M.Tech. degree in Electrical Engineering from IIT Bombay, Mumbai, India in 2014 where he is recipient of Postgraduate Color. He worked as an Engineer with TSMC Limited, Hsinchu, Taiwan, from 2015 to 2016. His research interests are related to multi-temporal and multi-sensor satellite image analysis, uncertainty quantification, deep learning, and climate change.

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Editorial
Elsevier - Health Sciences Division
Año de publicación
2025
Idioma
Inglés
ISBN 10 
0443264848
ISBN 13 
9780443264849
Encuadernación
Tapa blanda
Número de páginas
452
Editor
Saha Sudipan
Contacto del fabricante
ELSEVIER
https://www.elsevier.com/es-es

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