Chia-Hung Lin

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 43 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 26 citations into it
• Artificial Intelligence — 22 citations into it
• Control and Systems Engineering — 20 citations into it
• Reinforcement Learning — 11 citations into it
• Model Architectures — 8 citations into it

Whom Chia-Hung Lin trusts overall

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

1. Kaiming He
2. Sergey Levine
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. X. Zhang
6. Yoshua Bengio
7. Diederik P. Kingma
8. Shaoqing Ren
9. Chelsea Finn
10. Yann LeCun

Papers from Chia-Hung Lin's perspective

Ordered by how strongly the researchers Chia-Hung Lin 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• The CoSTAR Block Stacking Dataset: Learning with Workspace Constraints (2018) — 14 citations