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Название: Hyperspectral Image Analysis: Advances in Machine Learning and Signal Processing
Автор: Editors: Prasad, Saurabh, Chanussot, Jocelyn
Издательство: Springer
Год: 2020
Формат: True PDF
Страниц: 464
Размер: 17.4 Mb
Язык: English
This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas.
Автор: Editors: Prasad, Saurabh, Chanussot, Jocelyn
Издательство: Springer
Год: 2020
Формат: True PDF
Страниц: 464
Размер: 17.4 Mb
Язык: English
This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas.