3 citations · 8 across the 7 of their papers we have counts for
5 papers · 1 filter
Towards Generalizable Medical Image Segmentation with Pixel-wise Uncertainty Estimation
Shuai Wang, Zipei Yan, Daoan Zhang +4
Deep neural networks (DNNs) achieve promising performance in visual recognition under the independent and identically distributed (IID) hypothesis. In contrast, the IID hypothesis…
Black-box Source-free Domain Adaptation via Two-stage Knowledge Distillation
Shuai Wang, Daoan Zhang, Zipei Yan +2
Source-free domain adaptation aims to adapt deep neural networks using only pre-trained source models and target data. However, accessing the source model still has a potential con…
Prototype Knowledge Distillation for Medical Segmentation with Missing Modality
Shuai Wang, Zipei Yan, Daoan Zhang +3
Multi-modality medical imaging is crucial in clinical treatment as it can provide complementary information for medical image segmentation. However, collecting multi-modal data in…
Bootstrap The Original Latent: Learning a Private Model from a Black-box Model
Shuai Wang, Daoan Zhang, Jianguo Zhang +2
In this paper, considering the balance of data/model privacy of model owners and user needs, we propose a new setting called Back-Propagated Black-Box Adaptation (BPBA) for users t…
Feature Alignment and Uniformity for Test Time Adaptation
Shuai Wang, Daoan Zhang, Zipei Yan +2
Test time adaptation (TTA) aims to adapt deep neural networks when receiving out of distribution test domain samples. In this setting, the model can only access online unlabeled te…