文章基本信息

标题：Semi-supervised learning through hierarchical clustering for interactive aerospace image analysis
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作者：Sergey Rylov
期刊名称：E3S Web of Conferences
印刷版ISSN：2267-1242
电子版ISSN：2267-1242
出版年度：2019
卷号：75
页码：1-6
DOI：10.1051/e3sconf/20197501009
出版社：EDP Sciences
摘要：A new semi-supervised classification algorithm based on the non-parametric clustering algorithm HCA is proposed. The algorithm obtains hierarchical segmentation result where additional classes that are not represented in the training samples can be found. High performance of the algorithm allows using it in interactive mode. Experimental studies confirm that the proposed algorithm provides aerospace image classification in conditions of limited number of training samples.
其他摘要：A new semi-supervised classification algorithm based on the non-parametric clustering algorithm HCA is proposed. The algorithm obtains hierarchical segmentation result where additional classes that are not represented in the training samples can be found. High performance of the algorithm allows using it in interactive mode. Experimental studies confirm that the proposed algorithm provides aerospace image classification in conditions of limited number of training samples.