55 citations · 270 across the 30 of their papers we have counts for
8 papers · 1 filter
Relational Experience Replay: Continual Learning by Adaptively Tuning Task-wise Relationship
Quanziang Wang, Renzhen Wang, Yuexiang Li +4
Continual learning is a promising machine learning paradigm to learn new tasks while retaining previously learned knowledge over streaming training data. Till now, rehearsal-based…
A Unified Framework for Generalized Low-Shot Medical Image Segmentation with Scarce Data
Hengji Cui, Dong Wei, Kai Ma +2
Medical image segmentation has achieved remarkable advancements using deep neural networks (DNNs). However, DNNs often need big amounts of data and annotations for training, both o…
Unsupervised Representation Learning Meets Pseudo-Label Supervised Self-Distillation: A New Approach to Rare Disease Classification
Jinghan Sun, Dong Wei, Kai Ma +2
Rare diseases are characterized by low prevalence and are often chronically debilitating or life-threatening. Imaging-based classification of rare diseases is challenging due to th…
Training Automatic View Planner for Cardiac MR Imaging via Self-Supervision by Spatial Relationship between Views
Dong Wei, Kai Ma, Yefeng Zheng
View planning for the acquisition of cardiac magnetic resonance imaging (CMR) requires acquaintance with the cardiac anatomy and remains a challenging task in clinical practice. Ex…
Multi-Anchor Active Domain Adaptation for Semantic Segmentation
Munan Ning, Donghuan Lu, Dong Wei +5
Unsupervised domain adaption has proven to be an effective approach for alleviating the intensive workload of manual annotation by aligning the synthetic source-domain data and the…
A New Bidirectional Unsupervised Domain Adaptation Segmentation Framework
Munan Ning, Cheng Bian, Dong Wei +5
Domain shift happens in cross-domain scenarios commonly because of the wide gaps between different domains: when applying a deep learning model well-trained in one domain to anothe…