Artificial intelligence techniques for satellite image analysis / D. Jude Hemanth, editor.
Hemanth, D. Jude, editor.
2020
G70.4
Available Online

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Title Artificial intelligence techniques for satellite image analysis / D. Jude Hemanth, editor.
ISBN 9783030241780 (electronic book)
3030241785 (electronic book)
9783030241773
DOI https://doi.org/10.1007/978-3-030-24178-0
Published Cham, Switzerland : Springer, [2020].
Language English
Description 1 online resource (viii, 274 pages) : illustrations.
Item Number 10.1007/978-3-030-24178-0 doi
Call Number G70.4
Dewey Decimal Classification 910.28563
Summary The main objective of this book is to provide a common platform for diverse concepts in satellite image processing. In particular it presents the state-of-the-art in Artificial Intelligence (AI) methodologies and shares findings that can be translated into real-time applications to benefit humankind. Interdisciplinary in its scope, the book will be of interest to both newcomers and experienced scientists working in the fields of satellite image processing, geo-engineering, remote sensing and Artificial Intelligence. It can be also used as a supplementary textbook for graduate students in various engineering branches related to image processing.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed November 20, 2019).
Added Author Hemanth, D. Jude, editor.
Series Remote sensing and digital image processing ; v. 24.
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1. Heightening satellite image display via mobile augmented reality
a cutting-edge planning model.- 2. Multithreading Approach for clustering of Multi-Plane Satellite Images.- 3. Classification of field level crop types with a time series satellite data using Deep Neural Network.- 4. Detection of ship from satellite images using deep convolutional neural networks with improved median filter.- 5. Artificial Bee Colony optimized contrast enhancement for satellite image fusion.- 6. Effective transform domain denoising of oceanographic sar images for improved target characterization.- 7. Fused segmentation algorithm for the detection of nutrient deficiency in crops using SAR images.- 8. Detection of natural features and objects in satellite images by semantic segmentation using neural networks.- 9. Change Detection of Tropical Mangrove Ecosystem with Subpixel Classification of Time Series Hyperspectral Imagery.- 10. Crop Classification and Mapping for Agricultural Land from Satellite Images.- 11. Next Generation Artificial Intelligence Techniques for Satellite Data Processing.- 12. A wavelet transform applied spectral index for effective water body extraction from moderate resolution satellite images.

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