Dong Wook Shu

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 49 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 29 citations into it; #9,978 of 21,575 by trust here, #17,258 by citations
• Computational Mechanics — 13 citations into it; #4,055 of 10,001 by trust here, #6,877 by citations
• Artificial Intelligence — 9 citations into it
• Aerospace Engineering — 7 citations into it
• Graph Learning — 7 citations into it

Whom Dong Wook Shu trusts overall

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

1. Christian Szegedy
2. Geoffrey E. Hinton
3. Charles Ruizhongtai Qi
4. Alex Krizhevsky
5. Thomas Kipf
6. Yann LeCun
7. Diederik P. Kingma
8. Yoshua Bengio
9. Sanjoy Dasgupta
10. Kaiming He

Who trusts Dong Wook Shu overall

1. Julian Chibane
2. Shitong Luo
3. Abdul Jabbar
4. Xiaohui Zeng
5. Ruojin Cai
6. Gerard Pons-Moll
7. Wei Hu
8. Aymen Mir
9. Thiemo Alldieck
10. Xi Li

Papers from Dong Wook Shu's perspective

Ordered by how strongly the researchers Dong Wook Shu 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• 3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions (2019) — 342 citations