Steve Lin

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 174 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 31 citations into it
• Model Architectures — 14 citations into it
• Artificial Intelligence — 13 citations into it

Whom Steve Lin trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Shaoqing Ren
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Tsung-Yi Lin
7. David G. Lowe
8. Piotr Doll'ar
9. Yann LeCun
10. Jia Deng

Papers from Steve Lin's perspective

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

Their papers

• Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation (2019) — 73 citations