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Change Detection and Image Time Series Analysis 2 : Supervised Methods, Hardback Book

Change Detection and Image Time Series Analysis 2 : Supervised Methods Hardback

Edited by Abdourrahmane M. Atto, Francesca Bovolo, Lorenzo (University of Trento, Italy) Bruzzone

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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.

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£137.95

Available to Order - This title is available to order, with delivery expected within 2 weeks
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