Nengyuan Liu

Computer Vision and Pattern Recognition · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 52 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 19 citations into it
• Artificial Intelligence — 16 citations into it

Whom Nengyuan Liu trusts overall

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

1. Ross B. Girshick
2. Kaiming He

Papers from Nengyuan Liu's perspective

Ordered by how strongly the researchers Nengyuan 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet Large Scale Visual Recognition Challenge
6. ImageNet: A large-scale hierarchical image database
7. Going deeper with convolutions
8. Attention is All you Need (Neural Information Processing Systems)
9. Long Short-Term Memory
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Class Boundary Exemplar Selection Based Incremental Learning for Automatic Target Recognition (2020) — 53 citations
• Dense Attention Pyramid Networks for Multi-Scale Ship Detection in SAR Images (2019) — 419 citations