Synthetic Aperture Radar (SAR) Data Applications (Hardcover, 1st ed. 2023)

This carefully curated volume presents an in-depth, state-of-the-art discussion on many applications of Synthetic Aperture Radar (SAR). Integrating interdisciplinary sciences, the book features novel ideas, quantitative methods, and research results, promising to advance computational practices and technologies within the academic and industrial communities. SAR applications employ diverse and often complex computational methods rooted in machine learning, estimation, statistical learning, inversion models, and empirical models. Current and emerging applications of SAR data for earth observation, object detection and recognition, change detection, navigation, and interference mitigation are highlighted. Cutting edge methods, with particular emphasis on machine learning, are included. Contemporary deep learning models in object detection and recognition in SAR imagery with corresponding feature extraction and training schemes are considered. State-of-the-art neural network architectures in SAR-aided navigation are compared and discussed further. Advanced empirical and machine learning models in retrieving land and ocean information - wind, wave, soil conditions, among others, are also included.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Springer Optimization and Its Applications, 199
Release date:	2023
First published:	2022
Editors:	Maciej Rysz • Arsenios Tsokas • Kathleen M. Dipple • Kaitlin L. Fair • Panos M. Pardalos
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	278
Edition:	1st ed. 2023
ISBN-13:	978-3-03-121224-6
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Science & Mathematics > Mathematics > Optimization > General Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Promotions
LSN:	3-03-121224-X
Barcode:	9783031212246

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