E-Books →Atto A Change Detection and Image Time Series Analysis 1 2021
Published by: Emperor2011 on 6-09-2022, 15:39 | 
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Atto A Change Detection and Image Time Series Analysis 1 2021 | 33.3 MB
English | 293 Pages
Title: Change Detection and Image Time Series Analysis 1
Author: Abdourrahmane M. Atto
Year: 2021
Description:
Change Detection and Image Time Series Analysis 1 presents a wide range of unsupervised methods for temporal evolution analysis through the use of image time series associated with optical and/or synthetic aperture radar acquisition modalities.
Chapter 1 introduces two unsupervised approaches to multiple-change detection in bi-temporal multivariate images, with Chapters 2 and 3 addressing change detection in image time series in the context of the statistical analysis of covariance matrices. Chapter 4 focuses on wavelets and convolutional-neural filters for feature extraction and entropy-based anomaly detection, and Chapter 5 deals with a number of metrics such as cross correlation ratios and the Hausdorff distance for variational analysis of the state of snow. Chapter 6 presents a fractional dynamic stochastic field model for spatio temporal forecasting and for monitoring fast-moving meteorological events such as cyclones. Chapter 7 proposes an analysis based on characteristic points for texture modeling, in the context of graph theory, and Chapter 8 focuses on detecting new land cover types by classification-based change detection or feature/pixel based change detection. Chapter 9 focuses on the modeling of classes in the difference image and derives a multiclass model for this difference image in the context of change vector analysis.
DOWNLOAD:
https://rapidgator.net/file/063556c41b39d3b111c0bd6229bc0e72/Atto_A._Change_Detection_and_Image_Time_Series_Analysis_1._2021.rar
https://uploadgig.com/file/download/25513d266D22df15/Atto_A._Change_Detection_and_Image_Time_Series_Analysis_1._2021.rar
Change Detection and Image Time Series Analysis 1 presents a wide range of unsupervised methods for temporal evolution analysis through the use of image time series associated with optical and/or synthetic aperture radar acquisition modalities.
Chapter 1 introduces two unsupervised approaches to multiple-change detection in bi-temporal multivariate images, with Chapters 2 and 3 addressing change detection in image time series in the context of the statistical analysis of covariance matrices. Chapter 4 focuses on wavelets and convolutional-neural filters for feature extraction and entropy-based anomaly detection, and Chapter 5 deals with a number of metrics such as cross correlation ratios and the Hausdorff distance for variational analysis of the state of snow. Chapter 6 presents a fractional dynamic stochastic field model for spatio temporal forecasting and for monitoring fast-moving meteorological events such as cyclones. Chapter 7 proposes an analysis based on characteristic points for texture modeling, in the context of graph theory, and Chapter 8 focuses on detecting new land cover types by classification-based change detection or feature/pixel based change detection. Chapter 9 focuses on the modeling of classes in the difference image and derives a multiclass model for this difference image in the context of change vector analysis.
DOWNLOAD:
https://rapidgator.net/file/063556c41b39d3b111c0bd6229bc0e72/Atto_A._Change_Detection_and_Image_Time_Series_Analysis_1._2021.rar
https://uploadgig.com/file/download/25513d266D22df15/Atto_A._Change_Detection_and_Image_Time_Series_Analysis_1._2021.rar
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