A Novel Change Detection Approach for Multi-Temporal High-Resolution Remote Sensing Images Based on Rotation Forest and Coarse-to-Fine Uncertainty Analyses
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Title
A Novel Change Detection Approach for Multi-Temporal High-Resolution Remote Sensing Images Based on Rotation Forest and Coarse-to-Fine Uncertainty Analyses
Authors
Keywords
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Journal
Remote Sensing
Volume 10, Issue 7, Pages 1015
Publisher
MDPI AG
Online
2018-06-25
DOI
10.3390/rs10071015
References
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- (2016) Feng Gao et al. Journal of Applied Remote Sensing
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- Unsupervised Change Detection With Expectation-Maximization-Based Level Set
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- Change detection from remotely sensed images: From pixel-based to object-based approaches
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- ESP: a tool to estimate scale parameter for multiresolution image segmentation of remotely sensed data
- (2010) Lucian Drǎguţ et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- Unsupervised Change Detection in Satellite Images Using Principal Component Analysis and $k$-Means Clustering
- (2009) Turgay Celik IEEE Geoscience and Remote Sensing Letters
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