| 多视角半监督分类算法： 最新进展与比较研究 |
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| 引用本文： | 王石平,郭文忠,姚杰.多视角半监督分类算法： 最新进展与比较研究[J].福州大学学报(自然科学版),2021,49(5):626-637. |
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| 作者姓名： | 王石平 郭文忠 姚杰 |
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| 作者单位： | 福州大学,福州大学,福州大学 |
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| 基金项目： | 国家自然科学基金项目（面上项目，重点项目，重大项目） |
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| 摘 要： | 随着科技的发展，数据的获取渠道变得越来越多，所获得的数据也越来越多样化，多视角数据在目前的应用也已经相当普遍. 但是在处理真实世界的问题时，获得的多视角数据一般只带有少量标签，而人工标注的成本比较高昂，因此多视角半监督学习在机器学习和图像处理领域引起了许多学者的关注. 本文总结了近年来发表的多视角半监督分类方法并对这些方法进行了归类，对多视角半监督分类方法所面临的挑战进行了讨论.
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| 关 键 词： | 多视角 半监督学习 机器学习 图像处理 比较研究 |
| 收稿时间： | 2021/4/13 0:00:00 |
| 修稿时间： | 2021/6/8 0:00:00 |
Multi-view semi-supervised classification: latest development and comparative research |
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| Affiliation: | Fuzhou University,Fuzhou University,Fuzhou University |
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| Abstract: | With the development of science and technology, more and more channels are available for data acquisition, and the data obtained become more diversified. The current application of multi-view data has become quite common. However, when dealing with real-world problems, the multi-view data obtained often includes only a small number of labels, and the cost of manual labeling is relatively expensive, so multi-view semi-supervised learning has attracted the attention of many scholars in the field of machine learning and image processing. This article reviews and categorizes several multi-view semi-supervised classification methods published in recent years. Discuss the challenges faced by multi-view semi-supervised classification methods. |
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| Keywords: | multi-view semi-supervised learning machine learning image processing comparative research |
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