Deep Learning for Hyperspectral Image Analysis and Classification is popular PDF and ePub book, written by Linmi Tao in 2021-02-20, it is a fantastic choice for those who relish reading online the Computers genre. Let's immerse ourselves in this engaging Computers book by exploring the summary and details provided below. Remember, Deep Learning for Hyperspectral Image Analysis and Classification can be Read Online from any device for your convenience.
Deep Learning for Hyperspectral Image Analysis and Classification Book PDF Summary
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.
Detail Book of Deep Learning for Hyperspectral Image Analysis and Classification PDF
- Author : Linmi Tao
- Release : 20 February 2021
- Publisher : Springer Nature
- ISBN : 9789813344204
- Genre : Computers
- Total Page : 207 pages
- Language : English
- PDF File Size : 16,7 Mb
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