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Unsupervised and Semi-Supervised Learning

Unsupervised and Semi-Supervised Learning

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Unsupervised and Semi-Supervised Learning

Kawulok, Michal; Kawulok, Jolanta; Smolka, Bogdan; Celebi, M. Emre

This book provides a comprehensive perspective over the landscape of super-resolution techniques developed for and applied to remotely-sensed images. The chapters tackle the most important problems that professionals face when dealing with super-resolution in the context of remote sensing. These are: evaluation procedures to assess the super-resolution quality; benchmark datasets (simulated and real-life); super-resolution for specific data modalities (e.g., panchromatic, multispectral, and hyperspectral images); single-image super-resolution, including generative adversarial networks; multi-image fusion (temporal and/or spectral); real-world super-resolution; and task-driven super-resolution. The book presents the results of several recent surveys on super-resolution specifically for the remote sensing community.

Details

Published by: Springer

Publication Date: 2024-10-15

Format: Hardcover

ISBN-13: 9783031681059

DOI: 10.1007/978-3-031-68106-6

Dimensions: 235cm x155cm

Pages: 384

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