Xiaochun Ye

Computer Vision and Pattern Recognition · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 83 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 44 citations into it
• Artificial Intelligence — 37 citations into it
• Graph Learning — 12 citations into it

Whom Xiaochun Ye trusts overall

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

1. Ross B. Girshick
2. Karen Simonyan
3. Geoffrey E. Hinton
4. Kaiming He
5. Alex Krizhevsky
6. Andrew Zisserman
7. Yann LeCun
8. Yoshua Bengio
9. Diederik P. Kingma
10. Jia Deng

Papers from Xiaochun Ye's perspective

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

Their papers

• HyGCN: A GCN Accelerator with Hybrid Architecture (2020) — 351 citations
• C-MIDN: Coupled Multiple Instance Detection Network With Segmentation Guidance for Weakly Supervised Object Detection (2019) — 130 citations