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Retraining maximum likelihood classifiers using low-rank model.ppt

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Retraining maximum likelihood classifiers using a low-rank model Arnt-Børre Salberg Norwegian Computing Center Oslo, Norway IGARSS July 25, 2011
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Introduction ,[object Object],[object Object],[object Object],[object Object]
An existing method… ,[object Object],[object Object]
Low-rank parameter modeling ,[object Object],[object Object],[object Object],[object Object]
Low-rank data modeling ,[object Object],[object Object],[object Object]
Parameter estimation ,[object Object],[object Object]
Parameter estimation ,[object Object],[object Object],[object Object],[object Object]
Experiment 1: Cloud detection in optical images ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Experiment 1: Cloud detection in optical images ,[object Object],[object Object],average Test eigenvector
Experiment 1: Cloud detection in optical images ,[object Object],[object Object]
Results: Cloud detection in optical images Without retraining With retraining
Results: Cloud detection in optical images
Results: Cloud detection in optical images
Experiment 2: Tree cover mapping of tropical forest ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Experiment 2: Tree cover mapping of tropical forest ,[object Object],[object Object],[object Object]
Experiment 2: Tree cover mapping of tropical forest ,[object Object],[object Object]
Results: Tree cover mapping of tropical forest ,[object Object],Without retraining With retraining February 2010 July 2009
Summary and conclusion ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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