10 citations · 20 across the 6 of their papers we have counts for
9 papers
Learning to Learn Domain-invariant Parameters for Domain Generalization
Feng Hou, Yao Zhang, Yang Liu +6
Due to domain shift, deep neural networks (DNNs) usually fail to generalize well on unknown test data in practice. Domain generalization (DG) aims to overcome this issue by capturi…
Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation
Yao Zhang, Jiawei Yang, Jiang Tian +4
Liver cancer is one of the most common cancers worldwide. Due to inconspicuous texture changes of liver tumor, contrast-enhanced computed tomography (CT) imaging is effective for t…
ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities
Yixin Wang, Yang Zhang, Yang Liu +6
Accurate segmentation of brain tumors from magnetic resonance imaging (MRI) is clinically relevant in diagnoses, prognoses and surgery treatment, which requires multiple modalities…
Double-Uncertainty Weighted Method for Semi-supervised Learning
Yixin Wang, Yao Zhang, Jiang Tian +4
Though deep learning has achieved advanced performance recently, it remains a challenging task in the field of medical imaging, as obtaining reliable labeled training data is time-…
Disentangled Neural Architecture Search
Xinyue Zheng, Peng Wang, Qigang Wang +1
Neural architecture search has shown its great potential in various areas recently. However, existing methods rely heavily on a black-box controller to search architectures, which…
Challenge Closed-book Science Exam: A Meta-learning Based Question Answering System
Xinyue Zheng, Peng Wang, Qigang Wang +1
Prior work in standardized science exams requires support from large text corpus, such as targeted science corpus fromWikipedia or SimpleWikipedia. However, retrieving knowledge fr…