Deep Learning Algorithms for Satellite Imagery

Author:   Saikat Basu
Publisher:   Taylor & Francis Ltd
ISBN:  

9781138493650


Pages:   225
Publication Date:   15 December 2022
Format:   Hardback
Availability:   Not yet available   Availability explained
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Deep Learning Algorithms for Satellite Imagery


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Overview

This book provides key insights into the world of Deep Learning pertaining to satellite image understanding. It highlights what differentiates satellite image datasets from other natural or synthetic images and how to tackle problems specific to these imagery data. From answering questions like how to select optimal training data to weekly supervised and unsupervised learning and how to tackle loosely labeled data, it is a valuable source of information for anyone interested in understanding the theory behind satellite image analytics and provides key insights on the application of various state-of-the-art Deep Learning algorithms on these datasets.

Full Product Details

Author:   Saikat Basu
Publisher:   Taylor & Francis Ltd
Imprint:   CRC Press
ISBN:  

9781138493650


ISBN 10:   1138493651
Pages:   225
Publication Date:   15 December 2022
Audience:   College/higher education ,  Tertiary & Higher Education
Format:   Hardback
Publisher's Status:   Forthcoming
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

Unsupervised learning for satellite imagery. Working with loosely labeled data. Classification vs Segmentation. Semi-supervised learning. Using adversarial learning. Post-processing - Structured Prediction. Using hyperspectral images. Combining hand-crafted features and deep learning. Active Learning. Transfer Learning. Choosing optimal training data. Understanding relation between training data and optimal model size . Effect of data augmentation. Effects of skip connections for creating bigger networks. How satellite image processing differs from natural image processing.

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Author Information

Saikat Basu is working as a research scientist in the Facebook Maps team in Boston. He received his PhD in Computer Science from Louisiana State University in 2016. He received his Bachelor of Technology in Computer Science and Engineering from National Institute of Technology, Durgapur, India in 2011. During his doctoral program, he has been doing research on the analysis of various kinds of imagery data using Computer Vision and Deep Learning algorithms for the analysis of satellite imagery data. During his PhD, he has worked as a research associate at NASA Ames Research Center, Moffett Field, California and an intern at the Facebook Maps team in Boston.

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