Hu Peng

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 3 papers; trusts 63 researchers and is trusted by 25 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 58 citations into it; #5,530 of 21,575 by trust here, #9,563 by citations
• Media Technology — 56 citations into it; #447 of 3,621 by trust here, #757 by citations
• Aerospace Engineering — 10 citations into it; #4,223 of 6,421 by trust here, #4,388 by citations
• Biomedical Engineering — 5 citations into it
• Model Architectures — 5 citations into it

Whom Hu Peng trusts overall

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

1. Shutao Li
2. Bin Yang
3. Yu Liu
4. Gemma Piella
5. Yann LeCun
6. Evan Shelhamer
7. Zhongliang Jing
8. Yangqing Jia
9. Sergey Zagoruyko
10. Geoffrey E. Hinton

Who trusts Hu Peng overall

1. Jiayi Ma
2. Hui Li
3. Han Xu
4. Xiaojun Wu
5. Hao Zhang
6. Junjun Jiang
7. Wei Tang
8. Yu Liu
9. Linfeng Tang
10. Nantheera Anantrasirichai

Papers from Hu Peng's perspective

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

1. Gradient-based learning applied to document recognition
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Going deeper with convolutions
9. Fully convolutional networks for semantic segmentation
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Infrared and visible image fusion with convolutional neural networks (2017) — 417 citations
• A medical image fusion method based on convolutional neural networks (2017) — 370 citations
• Multi-focus image fusion with a deep convolutional neural network (2017) — 1,234 citations