Learning from label proportions for SAR image classification

Learning from label proportions for SAR image classification

Abstract Synthetic aperture radar (SAR) image classification plays a key role in SAR interpretation. Due to the cost and difficulty of truth labeling for SAR images, the newly labeled samples available for image classification are very limited. This paper focuses on defining a new sample labeling me...

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Bibliographic Details
Main Authors: Yongke Ding, Yuanxiang Li, Wenxian Yu
Format: Article
Language:English
Published: SpringerOpen 2017-05-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
SAR
Image classification
SVM
Label proportion
Land cover
Online Access:http://link.springer.com/article/10.1186/s13634-017-0478-8

Internet

http://link.springer.com/article/10.1186/s13634-017-0478-8

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