Jing Yuan

Computer Vision and Pattern Recognition · with Ayed · 2013–2018

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 38 citations into it

Whom Jing Yuan trusts overall

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

1. Kaiming He

Papers from Jing Yuan's perspective

Ordered by how strongly the researchers Jing Yuan trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Fully convolutional networks for semantic segmentation
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Densely Connected Convolutional Networks
5. Identity Mappings in Deep Residual Networks
6. Gradient-based learning applied to document recognition
7. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
8. Wide Residual Networks
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• HyperDense-Net: A Hyper-Densely Connected CNN for Multi-Modal Image Segmentation (2018) — 515 citations
• Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge (2013) — 882 citations