Tiange Luo

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 3 papers; trusts 516 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 86 citations into it
• Artificial Intelligence — 74 citations into it
• Representation & Self-Supervised Learning — 29 citations into it
• Radiology, Nuclear Medicine and Imaging — 14 citations into it
• Model Architectures — 10 citations into it
• Aerospace Engineering — 7 citations into it
• Optimization & Training — 6 citations into it

Whom Tiange Luo trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yann LeCun
6. David G. Lowe
7. Yoshua Bengio
8. Christian Szegedy
9. Diederik P. Kingma
10. Karen Simonyan

Who trusts Tiange Luo overall

1. Yisheng Song
2. Chunbo Lang
3. Shixiang Tang
4. Aoxue Li
5. Ting-Yuan Wang
6. Fan Zhang
7. Yue Chen
8. Wonpyo Park
9. Yixiong Zou
10. Gong Cheng

Papers from Tiange Luo's perspective

Ordered by how strongly the researchers Tiange Luo 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
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

• Learning to Navigate for Fine-grained Classification (2018) — 490 citations
• Few-Shot Learning With Global Class Representations (2019) — 121 citations
• Large-Scale Few-Shot Learning: Knowledge Transfer With Class Hierarchy (2019) — 140 citations