Generative Adversarial Networks for Remote Sensing
Amol Dattatraya Vibhute (u. a.)
ISBN 13: 9798369369005
Published by IGI Global, 2025
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Generative Adversarial Networks for Remote Sensing | Amol Dattatraya Vibhute (u. a.) | Buch | Englisch | 2025 | IGI Global | EAN 9798369369005 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 133486815
Synopsis:
Generative adversarial networks (GANs) are transforming the way complex remote sensing data is analyzed, offering innovative solutions for geospatial applications. Traditional methods often struggle to process high-dimensional remotely sensed datasets, leading to limitations in decision-making and predictive accuracy. By leveraging GANs, researchers can enhance feature extraction, object detection, and time-series analysis, enabling more precise environmental monitoring, urban planning, and agricultural assessments. This technological advancement not only improves real-time geospatial analysis but also opens new avenues for interdisciplinary collaboration, ethical considerations, and security challenges in AI-driven remote sensing. As GANs continue to evolve, their application in remote sensing holds the potential to drive sustainability and more informed global decision-making. Generative Adversarial Networks for Remote Sensing emphasizes the foundations of recent trends in GANs and remote sensing applications. It provides insights into the fundamentals of generative adversarial networks, historical advancements, novel GAN architectures and challenges in analyzing remote sensing data using GANs. Covering topics such as change detection, resource management, and feature engineering, this book is an excellent resource for geographers, geospatial data analysts, engineers, professionals, researchers, scholars, academicians, and more.
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Bibliographic Details
Title: Generative Adversarial Networks for Remote ...
Publisher: IGI Global
Publication Date: 2025
Binding: Buch
Condition: Neu