most citedDiffuseExpand: Expanding dataset for 2D medical image segmentation using diffusion models

8 citations · 14 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2023

MSE-Nets: Multi-annotated Semi-supervised Ensemble Networks for Improving Segmentation of Medical Image with Ambiguous Boundaries

Shuai Wang, Tengjin Weng, Jingyi Wang +6

Medical image segmentation annotations exhibit variations among experts due to the ambiguous boundaries of segmented objects and backgrounds in medical images. Although using multi…

cs.AI2023

SparseByteNN: A Novel Mobile Inference Acceleration Framework Based on Fine-Grained Group Sparsity

Haitao Xu, Songwei Liu, Yuyang Xu +7

To address the challenge of increasing network size, researchers have developed sparse models through network pruning. However, maintaining model accuracy while achieving significa…

cs.CR2023

Precise and Generalized Robustness Certification for Neural Networks

Yuanyuan Yuan, Shuai Wang, Zhendong Su

The objective of neural network (NN) robustness certification is to determine if a NN changes its predictions when mutations are made to its inputs. While most certification resear…

cs.SD2023

Adversarial Speaker Disentanglement Using Unannotated External Data for Self-supervised Representation Based Voice Conversion

Xintao Zhao, Shuai Wang, Yang Chao +2

Nowadays, recognition-synthesis-based methods have been quite popular with voice conversion (VC). By introducing linguistics features with good disentangling characters extracted f…

cs.LG2023

Meta-Reinforcement Learning Based on Self-Supervised Task Representation Learning

Mingyang Wang, Zhenshan Bing, Xiangtong Yao +5

Meta-reinforcement learning enables artificial agents to learn from related training tasks and adapt to new tasks efficiently with minimal interaction data. However, most existing…

cs.CV20232 cited

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…