342 citations · 706 across the 57 of their papers we have counts for
17 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…
Alleviating Noisy-label Effects in Image Classification via Probability Transition Matrix
Ziqi Zhang, Yuexiang Li, Hongxin Wei +3
Deep-learning-based image classification frameworks often suffer from the noisy label problem caused by the inter-observer variation. Recent studies employed learning-to-learn para…
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…
InDuDoNet: An Interpretable Dual Domain Network for CT Metal Artifact Reduction
Hong Wang, Yuexiang Li, Haimiao Zhang +4
For the task of metal artifact reduction (MAR), although deep learning (DL)-based methods have achieved promising performances, most of them suffer from two problems: 1) the CT ima…