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Deep Learning for Hyperspectral Image Analysis and Classification (Paperback, 1st ed. 2021)
Loot Price: R5,225
Discovery Miles 52 250
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Deep Learning for Hyperspectral Image Analysis and Classification (Paperback, 1st ed. 2021)
Series: Engineering Applications of Computational Methods, 5
Expected to ship within 10 - 15 working days
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This book focuses on deep learning-based methods for hyperspectral
image (HSI) analysis. Unsupervised spectral-spatial adaptive
band-noise factor-based formulation is devised for HSI noise
detection and band categorization. The method to characterize the
bands along with the noise estimation of HSIs will benefit
subsequent remote sensing techniques significantly. This book
develops on two fronts: On the one hand, it is aimed at domain
professionals who want to have an updated overview of how
hyperspectral acquisition techniques can combine with deep learning
architectures to solve specific tasks in different application
fields. On the other hand, the authors want to target the machine
learning and computer vision experts by giving them a picture of
how deep learning technologies are applied to hyperspectral data
from a multidisciplinary perspective. The presence of these two
viewpoints and the inclusion of application fields of remote
sensing by deep learning are the original contributions of this
review, which also highlights some potentialities and critical
issues related to the observed development trends.
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