SAR Image Retrieval Based on Unsupervised Domain Adaptation and Clustering

Famao Ye; Wei Luo; Meng Dong; Hailin He; Weidong Min

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SAR Image Retrieval Based on Unsupervised Domain Adaptation and Clustering

机译：基于无监督域自适应和聚类的SAR图像检索

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摘要

Efficiently retrieving synthetic aperture radar (SAR) image is an important yet challenging task in the remote sensing field. Due to the shortage of labeled SAR images for fine-tuning convolutional neural network (CNN) models, this letter presents an unsu

机译：在遥感领域，有效地提取合成孔径雷达（SAR）图像是一项重要而具有挑战性的任务。由于缺少用于微调卷积神经网络（CNN）模型的标记SAR图像，因此这封信表示

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来源
《IEEE Geoscience and Remote Sensing Letters》 |2019年第9期|1482-1486|共5页
作者
Famao Ye; Wei Luo; Meng Dong; Hailin He; Weidong Min;
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作者单位

School of Surveying and Mapping Engineering East China University of Technology Nanchang China;

School of Information Engineering Nanchang University Nanchang China;

School of Inf;

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正文语种 eng
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关键词
Synthetic aperture radar; Image retrieval; Training; Adaptation models; Feature extraction; Task analysis; Remote sensing;

机译：合成孔径雷达;图像检索;训练;适应模型;特征提取;任务分析;遥感;

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专利

1. Hierarchical Subspace Learning Based Unsupervised Domain Adaptation for Cross-Domain Classification of Remote Sensing Images [J] . Biplab Banerjee, Subhasis Chaudhuri Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of . 2017,第11期

机译：基于分层子空间学习的无监督域自适应遥感影像跨域分类
2. Gabor Feature Based Unsupervised Change Detection of Multitemporal SAR Images Based on Two-Level Clustering [J] . Li Heng-Chao, Celik Turgay, Longbotham Nathan, Geoscience and Remote Sensing Letters, IEEE . 2015,第12期

机译：基于两级聚类的基于Gabor特征的多时相SAR图像无监督变化检测
3. Unsupervised change detection in SAR images based on frequency difference and a modified fuzzy c-means clustering [J] . Yan Weidong, Shi Shaojun, Pan Lulu, International journal of remote sensing . 2018,第9a10期

机译：基于频率差和改进的模糊c均值聚类的SAR图像无监督变化检测
4. Unsupervised change detection in multitemporal SAR images via NSCT-domain feature clustering [C] . Sun Qiang, Gao Yong IEEE International Conference on Signal Processing, Communications and Computing . 2013

机译：通过NSCT域特征聚类的多时相SAR图像的无监督变化检测
5. Image annotation and retrieval based on multi-modal feature clustering and similarity propagation. [D] . Ben Ismail, Mohamed Maher. 2011

机译：基于多模式特征聚类和相似度传播的图像标注和检索。
6. Unsupervised Domain Adaptation for Classification of Histopathology Whole-Slide Images [O] . Jian Ren, Ilker Hacihaliloglu, Eric A. Singer, 2019

机译：用于组织病理学全幻灯片图像分类的无监督域适应
7. CLUE: Cluster-based Retrieval of Images by Unsupervised Learning [O] . Yixin Chen, James Z. Wang, Robert Krovetz 2003

机译：CLUE：基于群集的无监督学习图像检索
8. Enhancement of Tropical Land Cover Mapping with Wavelet-Based Fusion and Unsupervised Clustering of SAR and Landsat Image Data [R] . LeMoigne, J. , Laporte, N. , Netanyahuy, N. S. 2001

机译：基于小波变换和saR和Landsat图像数据无监督聚类的热带地形覆盖制图

SAR Image Retrieval Based on Unsupervised Domain Adaptation and Clustering

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