Yemin Shi

Computer Vision and Pattern Recognition · 2016–2019

A researcher in the Science corpus: 2 papers; trusts 228 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 59 citations into it
• Artificial Intelligence — 49 citations into it
• Model Architectures — 19 citations into it
• Representation & Self-Supervised Learning — 15 citations into it
• Optimization & Training — 12 citations into it

Whom Yemin Shi trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Karen Simonyan
4. Kaiming He
5. Yoshua Bengio
6. Christian Szegedy
7. Diederik P. Kingma
8. Andrew Zisserman
9. Sergey Ioffe
10. Yann LeCun

Who trusts Yemin Shi overall

1. Dongliang He
2. Zehua Sun
3. Wenhao Wu
4. Shuyang Sun
5. Jun Liu

Papers from Yemin Shi's perspective

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

Their papers

• Learning Long-Term Dependencies for Action Recognition with a Biologically-Inspired Deep Network (2016) — 65 citations
• Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning (2019) — 197 citations