Li Song

with Li · 2017

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

Whom Li Song trusts overall

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

1. Gisle Bjøntegaard
2. Kaiming He
3. Jiwon Kim
4. Yuanying Dai

Papers from Li Song's perspective

Ordered by how strongly the researchers Li Song 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. Gradient-based learning applied to document recognition
4. Going deeper with convolutions
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
9. Accurate Image Super-Resolution Using Very Deep Convolutional Networks
10. ImageNet: A large-scale hierarchical image database

Their papers

• CNN based post-processing to improve HEVC (2017) — 37 citations