In this paper, we investigate the application of semi-supervised learning approaches and particularly focus on the small sample size problem.
Jun 1, 2024 · This paper compares multilook Polarimetric SAR (PolSAR) image classification using three types of learning: a supervised, an unsupervised and a ...
We propose different strategies within self-training on how to select more reliable candidates from the pool of unlabeled samples to speed-up the learning ...
Semi-Supervised Learning for Ill-Posed Polarimetric SAR Classification. Year of publication. 2014. Authors.
This paper proposes a semi-supervised method to overcome both shortcomings. The data is analysed by an un-supervised clustering algorithm under the usage of all ...
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The application of semi- supervised learning in this thesis is motivated by ill-posed classification tasks related to the small training size problem. Therefore ...
Kiranyaz, “Semi-supervised learning for Ill-posed polarimetric SAR classification,” Remote Sens., vol. 6, no. 6, pp. 4801–. 4830, 2014. [15] X. Niu and Y ...
Journal of Machine Learning Research 2023. Semi-Supervised Learning for Ill-Posed Polarimetric SAR Classification. Peer-reviewed. Open access. DOI.
Semisupervised Classification with Adaptive Anchor Graph for PolSAR Images · Deep Fuzzy Graph Convolutional Networks for PolSAR Imagery Pixelwise Classification.
Conclusions: It proves that our method can effectively improve the SAR-ATR accuracy despite the deficiency of the labelled samples. Key words: SAR image ...