Xiahai Zhuang
Computer Vision and Pattern Recognition · 2013–2021
A researcher in the Science corpus: 6 papers; trusts 26 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 66 citations into it; #10,677 of 21,575 by trust here, #10,334 by citations
- Radiology, Nuclear Medicine and Imaging — 26 citations into it
- Biophysics — 14 citations into it
- Artificial Intelligence — 12 citations into it
- Biomedical Engineering — 12 citations into it
- Media Technology — 11 citations into it
- Cardiology and Cardiovascular Medicine — 7 citations into it
Whom Xiahai Zhuang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Daniel Rueckert
- Caroline Petitjean
- Yongyue Zhang
- M. Balafar
- Paul Yushkevich
- Juan Shen
- Jean-Nicolas Dacher
- M. Brady
- Alejandro F Frangi
- A. de Juan
Who trusts Xiahai Zhuang overall
- Cheng Chen
- Qi-Yan Dou
- Krishna Chaitanya
- Rushi Jiao
- Xiaofeng Liu
- Agisilaos Chartsias
- Ling Zhang
- Ertunç Erdil
- Yichi Zhang
- Chaehwa Yoo
Papers from Xiahai Zhuang's perspective
Ordered by how strongly the researchers Xiahai Zhuang trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- ImageNet: A large-scale hierarchical image database
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Fully convolutional networks for semantic segmentation
- Attention is All you Need (Neural Information Processing Systems)
- Going deeper with convolutions
Their papers
- Cardiac Image Super-Resolution with Global Correspondence Using Multi-Atlas PatchMatch (2013) — 264 citations
- Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge (2019) — 346 citations
- Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge (2021) — 467 citations
- A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging (2020) — 478 citations
- Multivariate Mixture Model for Myocardial Segmentation Combining Multi-Source Images (2016) — 384 citations
- Multi-scale patch and multi-modality atlases for whole heart segmentation of MRI (2016) — 512 citations