Change Detection and Image Time Series Analysis 2 : Supervised Methods Hardback
Edited by Abdourrahmane M. Atto, Francesca Bovolo, Lorenzo (University of Trento, Italy) Bruzzone
Hardback
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Description
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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Available to Order - This title is available to order, with delivery expected within 2 weeks
- Format:Hardback
- Pages:272 pages
- Publisher:ISTE Ltd
- Publication Date:04/01/2022
- Category:
- ISBN:9781789450576
Information
-
Available to Order - This title is available to order, with delivery expected within 2 weeks
- Format:Hardback
- Pages:272 pages
- Publisher:ISTE Ltd
- Publication Date:04/01/2022
- Category:
- ISBN:9781789450576