In this work, we enhance the generalization performance by proposing two strategies including knowledge accumulation and distribution enhancement for multi-source domain generalization person re-ID. Specifically, we encourage the learning of semantically significant features globally by establishing a simple ...
Domain adaptation for object detection has been extensively studied in recent years. Most existing approaches focus on single-source unsupervised domain ad... D Zhang,M Ye,Y Liu,... - 《Information Fusion》 被引量: 0发表: 2022年 Unified Domain Generalization and Adaptation for Multi-View 3D ...
Domain generalization for activity recognition via adaptive feature fusion. ACM Trans. Intell. Syst. Technol.https://doi.org/10.1145/3552434 (2022) (Just Accepted). Article Google Scholar Kong, Y. S., Suresh, V., Soh, J. & Ong, D. C. A systematic evaluation of domain adaptation in ...
We validate the proposed framework on multi-source cross-domain sentiment classification datasets in Chinese and English. The experimental results demonstrate that the proposed method is more effective than state-of-the-art methods in improving accuracy and generalization capability....
Fei-Fei. Fine-grained recogni- tion in the wild: A multi-task domain adaptation approach. arXiv preprint arXiv:1709.02476, 2017. 2 [13] M. Ghifary, W. Bastiaan Kleijn, M. Zhang, and D. Balduzzi. Domain generalization for object recognition with multi-task autoencoders. In Proceedings of...
These characteristics reflect the generalization of effect range based data representation. Here, the generalized data representation is introduced to overcome the defect of insufficient data coverage and accurately represent source data, which includes not only the value attributes of source data but also...
Transfer learning has ability to create learning task of weakly labeled or unlabeled target domain by using knowledge of source domain to help, which can e
Hence, these more sharable features improve the performance and generalization of the model on the target domain effectively.Background Recently, with the biomedical research development, an explosive amount of literature has been published online. As a result, it has brought a big challenge to the...
In most research, domain adaptation (DA) and domain generalization (DG) methods are frequently employed for RUL prediction under multiple or unknown operating conditions (Liao, Huang, Li, Chen, & Li, 2020). However, prediction models are constructed based on sufficient training instances of the ...
Therefore the success of supervised DAL in this “small sample” regime needs the effective utilization of the large amounts of unlabeled data to extract information that is useful for generalization. Toward this end, we here use the geometric intuition of manifold assumption to extend the ...