Ziyue Xu

Computer Vision and Pattern Recognition · 2014–2022

A researcher in the Science corpus: 7 papers; trusts 119 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 118 citations into it; #19,767 of 21,575 by trust here, #3,313 by citations
• Artificial Intelligence — 74 citations into it
• Evaluation & Benchmarks — 13 citations into it
• Natural Language Processing — 10 citations into it
• Representation & Self-Supervised Learning — 7 citations into it

Whom Ziyue Xu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Yoshua Bengio
5. Karen Simonyan
6. Diederik P. Kingma
7. Ilya Sutskever
8. Yann LeCun
9. Chin-Yew Lin
10. Ross B. Girshick

Who trusts Ziyue Xu overall

1. Chaopeng Shen
2. Mohammad Mustafa Taye

Papers from Ziyue Xu's perspective

Ordered by how strongly the researchers Ziyue Xu trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet: A large-scale hierarchical image database
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Going deeper with convolutions
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning (2016) — 5,088 citations
• MONAI: An open-source framework for deep learning in healthcare (2022) — 996 citations
• When Radiology Report Generation Meets Knowledge Graph (2020) — 410 citations
• Generalizing Deep Learning for Medical Image Segmentation to Unseen Domains via Deep Stacked Transformation (2020) — 514 citations
• Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities; Results of the WMH Segmentation Challenge (2019) — 315 citations
• Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation (2019) — 50 citations
• A Review on Segmentation of Positron Emission Tomography Images (2014) — 386 citations