Jing Liu

Computer Vision and Pattern Recognition · with Zhuang · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 237 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 112 citations into it
• Artificial Intelligence — 77 citations into it
• Efficiency & Compression — 52 citations into it
• Model Architectures — 19 citations into it
• Optimization & Training — 9 citations into it

Whom Jing Liu trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Karen Simonyan
5. Andrew Zisserman
6. Yann LeCun
7. Yoshua Bengio
8. Ross B. Girshick
9. Ilya Sutskever
10. Christian Szegedy

Who trusts Jing Liu overall

1. Yong Guo

Papers from Jing Liu's perspective

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

Their papers

• Discrimination-aware Channel Pruning for Deep Neural Networks (2018) — 637 citations
• Discrimination-Aware Network Pruning for Deep Model Compression (2020) — 169 citations