Truc Le

Computer Vision and Pattern Recognition · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 409 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 70 citations into it; #9,089 of 21,575 by trust here, #5,013 by citations
• Computational Mechanics — 27 citations into it; #3,534 of 10,001 by trust here, #5,350 by citations
• Media Technology — 24 citations into it
• Artificial Intelligence — 14 citations into it
• Model Architectures — 11 citations into it
• Computer Graphics and Computer-Aided Design — 10 citations into it
• Geology — 9 citations into it; #252 of 687 by trust here, #464 by citations
• Optimization & Training — 7 citations into it

Whom Truc Le trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Diederik P. Kingma
4. Kaiming He
5. Karen Simonyan
6. Christian Szegedy
7. Sergey Ioffe
8. Ilya Sutskever
9. Yann LeCun
10. Andrew Zisserman

Who trusts Truc Le overall

1. Zhiyuan Zhang
2. Linqi Zhou
3. Haoshu Fang
4. Binh-Son Hua
5. Yilun Du
6. Chenxi Wang
7. Sai-Kit Yeung
8. Jiajun Wu
9. Minghao Gou

Papers from Truc Le's perspective

Ordered by how strongly the researchers Truc Le 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 classification with deep convolutional neural networks
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. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results (2017) — 1,901 citations
• PointGrid: A Deep Network for 3D Shape Understanding (2018) — 408 citations