多视角半监督分类算法比较及研究进展

Comparison and research progress of multi-view semi-supervised classification algorithms

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.本研究对近年来提出的多视角半监督分类方法进行归类,并对多视角半监督分类方法所面临的挑战进行讨论.

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.