Naifan Zhuang

Computer Vision and Pattern Recognition · 2015

A researcher in the Science corpus: 1 paper; trusts 65 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 29 citations into it; #5,965 of 21,575 by trust here, #7,852 by citations
• Artificial Intelligence — 11 citations into it; #8,616 of 35,345 by trust here, #11,192 by citations
• Biomedical Engineering — 9 citations into it; #1,039 of 10,734 by trust here, #3,600 by citations
• Human-Computer Interaction — 7 citations into it
• Model Architectures — 7 citations into it; #694 of 2,278 by trust here, #1,092 by citations

Whom Naifan Zhuang trusts overall

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

1. Sepp Hochreiter
2. Moez Baccouche
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Ilya Sutskever
6. J. Urgen Schmidhuber
7. Alex Graves
8. Jeff Donahue
9. Yoshua Bengio
10. Ivan Laptev

Who trusts Naifan Zhuang overall

1. Pichao Wang
2. Jun Liu
3. Qiuhong Ke
4. Guillermo Garcia-Hernando
5. Wanqing Li
6. Hongsong Wang
7. Amir Shahroudy
8. Mohammed Bennamoun
9. Diogo Carbonera Luvizon
10. Ke Cheng

Papers from Naifan Zhuang's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Long Short-Term Memory
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Differential Recurrent Neural Networks for Action Recognition (2015) — 492 citations