10 papers
Adaptive Hardness-driven Augmentation and Alignment Strategies for Multi-Source Domain Adaptations
Yang Yuxiang, Zeng Xinyi, Zeng Pinxian +4
Multi-source Domain Adaptation (MDA) aims to transfer knowledge from multiple labeled source domains to an unlabeled target domain. Nevertheless, traditional methods primarily focu…
BASIC: Semi-supervised Multi-organ Segmentation with Balanced Subclass Regularization and Semantic-conflict Penalty
Zhenghao Feng, Lu Wen, Yuanyuan Xu +4
Semi-supervised learning (SSL) has shown notable potential in relieving the heavy demand of dense prediction tasks on large-scale well-annotated datasets, especially for the challe…
Judge Like a Real Doctor: Dual Teacher Sample Consistency Framework for Semi-supervised Medical Image Classification
Zhang Qixiang, Yang Yuxiang, Zu Chen +4
Semi-supervised learning (SSL) is a popular solution to alleviate the high annotation cost in medical image classification. As a main branch of SSL, consistency regularization enga…
BTMuda: A Bi-level Multi-source unsupervised domain adaptation framework for breast cancer diagnosis
Yuxiang Yang, Xinyi Zeng, Pinxian Zeng +4
Deep learning has revolutionized the early detection of breast cancer, resulting in a significant decrease in mortality rates. However, difficulties in obtaining annotations and hu…
S3PET: Semi-supervised Standard-dose PET Image Reconstruction via Dose-aware Token Swap
Jiaqi Cui, Pinxian Zeng, Yuanyuan Xu +3
To acquire high-quality positron emission tomography (PET) images while reducing the radiation tracer dose, numerous efforts have been devoted to reconstructing standard-dose PET (…
Learning with Alignments: Tackling the Inter- and Intra-domain Shifts for Cross-multidomain Facial Expression Recognition
Yuxiang Yang, Lu Wen, Xinyi Zeng +4
Facial Expression Recognition (FER) holds significant importance in human-computer interactions. Existing cross-domain FER methods often transfer knowledge solely from a single lab…