Bruzzone m (23 Ergebnisse)

Paperback. Zustand: Brand New. edizioni minerva medica edition. 96 pages. 10.47x7.32x0.24 inches. In Stock.

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HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: As New. Unread book in perfect condition.

Zustand: As New. Unread book in perfect condition.

Zustand: New. In English.

Zustand: New. In English.

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Zustand: New.

Paperback. Zustand: Brand New. Italian language. 8.66x5.43x1.34 inches. In Stock.

Zustand: New. Abdourrahmane M. Atto is Associate Professor at the University Savoie Mont Blanc, France. His research interests include mathematical methods and models for artificial intelligence and image time series.Francesca Bovolo is the Head of the Remote Sensing for.

Zustand: New. Abdourrahmane M. Atto is Associate Professor at the University Savoie Mont Blanc, France. His research interests include mathematical methods and models for artificial intelligence and image time series.Francesca Bovolo is the Head of the Remote Sensing for.

Hardcover. Zustand: Brand New. 266 pages. 9.53x6.50x0.91 inches. In Stock.

Hardcover. Zustand: Brand New. 296 pages. 9.53x6.46x0.83 inches. In Stock.

Zustand: New. 2022. 1st Edition. Hardback. . . . . . Books ship from the US and Ireland.

Zustand: New. 2022. 1st Edition. Hardback. . . . . . Books ship from the US and Ireland.

Buch. Zustand: Neu. Neuware - Change Detection and Image Time Series Analysis 2 presents supervised machine-learning-based methods for temporal evolution analysis by using image time series associated with Earth observation data. Chapter 1 addresses the fusion of multisensor, multiresolution and multitemporal data. It proposes two supervised solutions that are based on a Markov random field: the first relies on a quad-tree and the second is specifically designed to deal with multimission, multifrequency and multiresolution time series.Chapter 2 provides an overview of pixel based methods for time series classification, from the earliest shallow learning methods to the most recent deep-learning-based approaches.Chapter 3 focuses on very high spatial resolution data time series and on the use of semantic information for modeling spatio-temporal evolution patterns.Chapter 4 centers on the challenges of dense time series analysis, including pre processing aspects and a taxonomy of existing methodologies. Finally, since the evaluation of a learning system can be subject to multiple considerations,Chapters 5 and 6 offer extensive evaluations of the methodologies and learning frameworks used to produce change maps, in the context of multiclass and/or multilabel change classification issues.…

Buch. Zustand: Neu. Neuware - 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.…

paperback. Zustand: Sehr gut. 24 Seiten; 9783765562655.2 Gewicht in Gramm: 500.

Zustand: Used: Very Good. Libro proveniente da collezione privata. Pagine ingiallite. La copertina riporta usuali segni del tempo. Consegna 24/48 ore 51 n7.