Jun Zhang

Computer Vision and Pattern Recognition · with Wang · 2019–2022

A researcher in the Science corpus: 2 papers; trusts 22 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 36 citations into it
• Artificial Intelligence — 26 citations into it
• Representation & Self-Supervised Learning — 9 citations into it

Whom Jun Zhang trusts overall

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

1. Manik Varma
2. Andrew Zisserman
3. Brendan J. Frey
4. Avrim Blum
5. Timo Ojala
6. Juan José Rodríguez Diez
7. Sergey Korolev
8. Geoffrey E. Hinton
9. Alex Krizhevsky
10. S. Chawla

Papers from Jun Zhang's perspective

Ordered by how strongly the researchers Jun Zhang 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
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. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Transformer-based unsupervised contrastive learning for histopathological image classification (2022) — 741 citations
• Group-Wise Learning for Aurora Image Classification With Multiple Representations (2019) — 11 citations