Amy Zhao

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 4 papers; trusts 340 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 130 citations into it; #8,999 of 21,575 by trust here, #6,873 by citations
• Artificial Intelligence — 29 citations into it
• Radiology, Nuclear Medicine and Imaging — 28 citations into it; #1,636 of 3,265 by trust here, #2,073 by citations
• Generative Models — 21 citations into it
• Aerospace Engineering — 16 citations into it
• Cognitive Neuroscience — 15 citations into it
• Biomedical Engineering — 14 citations into it; #2,277 of 10,734 by trust here, #5,019 by citations
• Media Technology — 10 citations into it

Whom Amy Zhao trusts overall

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

1. John Ashburner
2. Diederik P. Kingma
3. Bruce Fischl
4. Geoffrey E. Hinton
5. Karen Simonyan
6. Alex Krizhevsky
7. Thomas Brox
8. Olaf Ronneberger
9. Yann LeCun
10. Yoshua Bengio

Who trusts Amy Zhao overall

1. Adrian V. Dalca
2. Maithra Raghu
3. Guha Balakrishnan
4. Grant Haskins
5. Yabo Fu
6. Junyu Chen
7. Boah Kim
8. Tong Zhao
9. Chen Chen
10. John V. Guttag

Papers from Amy Zhao's perspective

Ordered by how strongly the researchers Amy Zhao 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. Gradient-based learning applied to document recognition
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Synthesizing Images of Humans in Unseen Poses (2018) — 327 citations
• VoxelMorph: A Learning Framework for Deformable Medical Image Registration (2018) — 2,150 citations
• An Unsupervised Learning Model for Deformable Medical Image Registration (2018) — 703 citations
• Data Augmentation Using Learned Transformations for One-Shot Medical Image Segmentation (2019) — 448 citations