most citedMMGL: Multi-Scale Multi-View Global-Local Contrastive learning for Semi-supervised Cardiac Image Segmentation

24 citations · 45 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2023

Wafer Map Defect Patterns Semi-Supervised Classification Using Latent Vector Representation

Qiyu Wei, Wei Zhao, Xiaoyan Zheng +1

As the globalization of semiconductor design and manufacturing processes continues, the demand for defect detection during integrated circuit fabrication stages is becoming increas…

cs.CV2023

A Deeply Supervised Semantic Segmentation Method Based on GAN

Wei Zhao, Qiyu Wei, Zeng Zeng

In recent years, the field of intelligent transportation has witnessed rapid advancements, driven by the increasing demand for automation and efficiency in transportation systems.…

q-bio.MN20232 cited

SemiGNN-PPI: Self-Ensembling Multi-Graph Neural Network for Efficient and Generalizable Protein-Protein Interaction Prediction

Ziyuan Zhao, Peisheng Qian, Xulei Yang +4

Protein-protein interactions (PPIs) are crucial in various biological processes and their study has significant implications for drug development and disease diagnosis. Existing de…

cs.CV20239 cited

Meta-hallucinator: Towards Few-Shot Cross-Modality Cardiac Image Segmentation

Ziyuan Zhao, Fangcheng Zhou, Zeng Zeng +2

Domain shift and label scarcity heavily limit deep learning applications to various medical image analysis tasks. Unsupervised domain adaptation (UDA) techniques have recently achi…

eess.IV202210 cited

ACT-Net: Asymmetric Co-Teacher Network for Semi-supervised Memory-efficient Medical Image Segmentation

Ziyuan Zhao, Andong Zhu, Zeng Zeng +2

While deep models have shown promising performance in medical image segmentation, they heavily rely on a large amount of well-annotated data, which is difficult to access, especial…

eess.IV202224 cited

MMGL: Multi-Scale Multi-View Global-Local Contrastive learning for Semi-supervised Cardiac Image Segmentation

Ziyuan Zhao, Jinxuan Hu, Zeng Zeng +4

With large-scale well-labeled datasets, deep learning has shown significant success in medical image segmentation. However, it is challenging to acquire abundant annotations in cli…