广东工业大学学报2025，Vol.42Issue(4)：59-70,12.DOI:10.12052/gdutxb.240096
基于域不变判别特征学习的深子域自适应方法
Deep Subdomain Adaptation Method Based on Domain Invariant Discriminant Feature Learning
摘要
Abstract
Unsupervised domain adaptation aims to transfer knowledge from labeled data in the source domain to the unlabeled target domain.The unsupervised domain adaptation method based on domain alignment learns domain invariant features by minimizing the difference in cross domain feature distribution,ignoring the learning of discriminative features in the target domain,resulting in poor discriminability of the learned domain invariant features in the target domain,confusion of different types of features,and performance decrease of the model.To address the problem of poor discriminative power of domain invariant features in the target domain during domain alignment,this paper proposes a deep Subdomain Adaptive method based on domain invariant Discriminative Feature learning(DFSA).The deep subdomain adaptive method is combined with the constraints of minimizing class confusion to increase the inter-class differences of domain invariant features,and consistency regularization is added to reduce the intra-class differences of domain invariant features.By doing so,domain invariant discriminative features are mined to better preserve the discriminative power of domain invariant features in the target domain and improve domain adaptability.The effectiveness of DFSA was validated on the Office-31 and Office-Home benchmark datasets,and the results showed that DFSA effectively improves domain adaptation performance,with an average accuracy improvement of approximately 0.79 percentage points and 3.51 percentage points,respectively,when compared with existing deep subdomain adaptation methods on the two benchmark datasets.关键词
深度学习/域自适应/判别特征学习/最小类混淆/一致性约束Key words
deep learning/domain adaptation/discriminant feature learning/minimum class confusion/consistency constrain分类
信息技术与安全科学引用本文复制引用
肖铠祥,吴晓鸰,冯永晋,Hoon Heo..基于域不变判别特征学习的深子域自适应方法[J].广东工业大学学报,2025,42(4):59-70,12.基金项目
广东省重点领域研发计划项目(2019B010139002) （2019B010139002）
广东省国际科技合作领域项目(2019A050513010) （2019A050513010）
