Cheng-En Wu

Computer Vision and Pattern Recognition · with Chen · 2019

A researcher in the Science corpus: 1 paper; trusts 31 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 33 citations into it; #14,956 of 21,575 by trust here, #7,249 by citations
• Artificial Intelligence — 25 citations into it; #24,172 of 35,345 by trust here, #10,319 by citations
• Representation & Self-Supervised Learning — 14 citations into it

Whom Cheng-En Wu trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Arun Mallya
4. Andrew Zisserman
5. Ilya Sutskever
6. Yoshua Bengio
7. Kaiming He
8. Yann LeCun
9. Diederik P. Kingma
10. Ross B. Girshick

Who trusts Cheng-En Wu overall

1. Sen Lin
2. Gyuhak Kim
3. Li Yang

Papers from Cheng-En Wu's perspective

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

Their papers

• Compacting, Picking and Growing for Unforgetting Continual Learning (2019) — 379 citations