Semisupervised SAR image change detection based on a siamese variational autoencoder
Authors:
- Guangwei ZhaoGZGuangwei Zhao
- Yaxin PengYPYaxin Peng
- 1 January 2022
- journal article
- research article
- Published by Elsevier in Information Processing & Management
- Vol. 59 (1)
Abstract
No abstract availableKeywords
This publication has 36 references indexed in Scilit:
- Unsupervised change detection in SAR images based on locally fitting model and semi-EM algorithmInternational Journal of Remote Sensing, 2014
- Fuzzy clustering algorithms incorporating local information for change detection in remotely sensed imagesApplied Soft Computing, 2012
- Fuzzy clustering algorithms for unsupervised change detection in remote sensing imagesInformation Sciences, 2011
- Reducing the Dimensionality of Data with Neural NetworksScience, 2006
- Evaluation of global image thresholding for change detectionPattern Recognition Letters, 2003
- An adaptive semiparametric and context-based approach to unsupervised change detection in multitemporal remote-sensing imagesIEEE Transactions on Image Processing, 2002
- Automatic analysis of the difference image for unsupervised change detectionIEEE Transactions on Geoscience and Remote Sensing, 2000
- SIGNATURE VERIFICATION USING A “SIAMESE” TIME DELAY NEURAL NETWORKInternational Journal of Pattern Recognition and Artificial Intelligence, 1993
- Minimum error thresholdingPattern Recognition, 1986
- Coefficient Kappa: Some Uses, Misuses, and AlternativesEducational and Psychological Measurement, 1981