Kwan-Yee Lin

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 30 citations into it

Whom Kwan-Yee Lin trusts overall

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

1. Ross B. Girshick
2. Evan Shelhamer
3. Kaiming He
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. X. Wang
7. Seungyong Lee
8. Junjun He

Who trusts Kwan-Yee Lin overall

1. Sheng Fang

Papers from Kwan-Yee Lin's perspective

Ordered by how strongly the researchers Kwan-Yee Lin 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. ImageNet: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Fully convolutional networks for semantic segmentation
7. Attention is All you Need (Neural Information Processing Systems)
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

• Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation (2020) — 449 citations