Lianghua He

Artificial Intelligence · with Liu · 2022

A researcher in the Science corpus: 1 paper; trusts 60 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Safety, Robustness & Interpretability — 7 citations into it
• Model Architectures — 6 citations into it

Whom Lianghua He trusts overall

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

1. Karen Simonyan
2. Kaiming He
3. Jia Deng
4. Oscar Li
5. Andrew Zisserman
6. Geoffrey E. Hinton
7. Alex Krizhevsky

Papers from Lianghua He's perspective

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

Their papers

• Decoupling Deep Learning for Interpretable Image Recognition (2022) — 6 citations