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Change Detection and Image Time-Series Analysis 1 Unervised Methods /
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 mul...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , , |
| Formato: | eBook |
| Idioma: | Inglés |
| Publicado: |
London :
Wiley-ISTE,
2022.
|
| Edición: | 1st edition. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
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| 020 | |a 1119882249 | ||
| 020 | |a 9781119882244 |z 9781789450569 |q (e-book) | ||
| 035 | |a (OCoLC)1289798417 | ||
| 037 | |a 9781789450569 |b O'Reilly Media | ||
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| 245 | 0 | 0 | |a Change Detection and Image Time-Series Analysis 1 |b Unervised Methods / |c edited by Abdourramahn Atto, Francesca Bovolo, Lorenzo Bruzzone. |
| 250 | |a 1st edition. | ||
| 264 | 1 | |a London : |b Wiley-ISTE, |c 2022. | |
| 300 | |a 1 online resource | ||
| 520 | |a 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. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Time-series analysis. | |
| 650 | 7 | |a Time-series analysis. |2 fast |0 (OCoLC)fst01151190 | |
| 700 | 1 | |a Atto, Abdourramahn, |e editor. | |
| 700 | 1 | |a Bovolo, Francesca, |e editor. | |
| 700 | 1 | |a Bruzzone, Lorenzo, |e editor. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781789450569/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 938 | |a Askews and Holts Library Services |b ASKH |n AH39547655 | ||
| 994 | |a 92 |b IZTAP | ||