Xin Yi

Computer Vision and Pattern Recognition · with Babyn · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 529 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 132 citations into it; #10,764 of 21,575 by trust here, #8,952 by citations
• Generative Models — 71 citations into it; #1,303 of 1,956 by trust here, #1,091 by citations
• Artificial Intelligence — 51 citations into it; #22,409 of 35,345 by trust here, #13,962 by citations
• Radiology, Nuclear Medicine and Imaging — 48 citations into it; #1,851 of 3,265 by trust here, #3,008 by citations
• Media Technology — 22 citations into it
• Biomedical Engineering — 16 citations into it; #6,154 of 10,734 by trust here, #9,794 by citations
• Biophysics — 15 citations into it
• Model Architectures — 14 citations into it

Whom Xin Yi trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Karen Simonyan
4. Kaiming He
5. Diederik P. Kingma
6. Yoshua Bengio
7. Yann LeCun
8. Individualized Treat
9. Ilya Sutskever
10. Andrew Zisserman

Who trusts Xin Yi overall

1. Sergey I. Nikolenko
2. Martin J. Willemink
3. Chetan L. Srinidhi
4. Peter B. Noël
5. Miaoyun Zhao
6. Evgin Göçeri
7. Luís Pinto-Coelho
8. Octavio Loyola-González
9. Ozan Ciga
10. Shiva Maleki Varnosfaderani

Papers from Xin Yi's perspective

Ordered by how strongly the researchers Xin Yi 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Generative Adversarial Network in Medical Imaging: A Review (2018) — 1,691 citations
• Sharpness-Aware Low-Dose CT Denoising Using Conditional Generative Adversarial Network (2017) — 319 citations