Qing Fu

Computer Vision and Pattern Recognition · with Deng · 2020

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 10 citations into it

Whom Qing Fu trusts overall

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

1. Olaf Ronneberger
2. Kaiming He

Papers from Qing Fu's perspective

Ordered by how strongly the researchers Qing Fu 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. Gradient-based learning applied to document recognition
4. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
5. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Learning Multiple Layers of Features from Tiny Images
8. Attention is All you Need (Neural Information Processing Systems)
9. Long Short-Term Memory
10. ImageNet: A large-scale hierarchical image database

Their papers

• A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT (2020) — 534 citations
• Deep Learning-based Detection for COVID-19 from Chest CT using Weak Label (2020) — 614 citations