Xiangbin Liu

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 101 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 47 citations into it
• Artificial Intelligence — 21 citations into it
• Radiology, Nuclear Medicine and Imaging — 17 citations into it
• Model Architectures — 9 citations into it
• Biomedical Engineering — 5 citations into it

Whom Xiangbin Liu trusts overall

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

1. Kaiming He
2. Karen Simonyan
3. Yann LeCun
4. Shaoqing Ren
5. Alex Krizhevsky
6. Geoffrey E. Hinton
7. Ross B. Girshick
8. Yoshua Bengio
9. Andrew Zisserman
10. Phi Vu Tran

Papers from Xiangbin Liu's perspective

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

Their papers

• A Review of Deep-Learning-Based Medical Image Segmentation Methods (2021) — 759 citations