南京师大学报（自然科学版）2026，Vol.49Issue(1)：96-107,12.DOI:10.3969/j.issn.1001-4616.2026.01.010
使用模糊标签驱动标签松弛的多视角分类算法
Multi-view Classification Driven by Fuzzy Labels for Label Relaxation
摘要
Abstract
With the continuous advancement of data acquisition technologies,multi-view data has been widely applied in fields such as medical imaging,action recognition,and multimodal analysis.However,semantic discrepancies across different views and subjectivity in the label annotation process often lead to label noise and reduced classification robustness.To address these issues,this paper proposed a multi-view classification algorithm that integrates fuzzy-label-driven label relaxation with consistency regularization.Specifically,fuzzy clustering was employed to construct soft label representations for each sample,aiming to capture the uncertainty and semantic ambiguity in the labels.During the learning of soft labels,the method introduced view-specific weights and joint constraints with ground-truth labels to guide the model in establishing a flexible supervision mechanism between hard and fuzzy labels,thereby achieving a smooth transition at the label level.Finally,through iterative optimization of both soft labels and view features,the model learned a discriminative feature projection matrix.Experimental results on four real-world multi-view datasets demonstrated that the proposed method outperforms conventional multi-view and traditional classification approaches in terms of robustness to label noise and effectiveness in multi-view information integration.关键词
多视角学习/模糊聚类/标签松弛/机器学习Key words
multi-view learning/fuzzy clustering/label relaxation/machine learning分类
信息技术与安全科学引用本文复制引用
邱成羽,陈秀,程煜婷,谢宇航,欧哲权,张远鹏..使用模糊标签驱动标签松弛的多视角分类算法[J].南京师大学报（自然科学版）,2026,49(1):96-107,12.基金项目
国家自然科学基金面上项目(82572382)、江苏高校"青蓝工程"项目、江苏省研究生科研与实践创新计划项目(KYCX24-3561). （82572382）
