Jun Yuan

Computer Vision and Pattern Recognition · with Alsallakh · 2020

A researcher in the Science corpus: 1 paper; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 19 citations into it
• Model Architectures — 12 citations into it

Whom Jun Yuan trusts overall

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

1. Karen Simonyan
2. Kaiming He
3. Geoffrey E. Hinton
4. Christian Szegedy
5. Hugo Larochelle
6. Andrew Zisserman

Papers from Jun Yuan's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Going deeper with convolutions
3. ImageNet classification with deep convolutional neural networks
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
6. Gradient-based learning applied to document recognition
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. Attention is All you Need (Neural Information Processing Systems)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Mind the Pad - CNNs can Develop Blind Spots (2020) — 85 citations