Zhenyong Fu

Computer Vision and Pattern Recognition · with Gong · 2014–2015

A researcher in the Science corpus: 2 papers; trusts 203 researchers and is trusted by 31 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 47 citations into it; #4,719 of 21,575 by trust here, #6,146 by citations
• Artificial Intelligence — 42 citations into it; #6,056 of 35,345 by trust here, #8,619 by citations
• Representation & Self-Supervised Learning — 19 citations into it; #810 of 3,145 by trust here, #1,138 by citations
• Natural Language Processing — 5 citations into it
• Radiology, Nuclear Medicine and Imaging — 5 citations into it

Whom Zhenyong Fu trusts overall

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

1. Tomas Mikolov
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Yann LeCun
6. Kaiming He
7. Robert Tibshirani
8. Ilya Sutskever
9. Diederik P. Kingma
10. Christoph H. Lampert

Who trusts Zhenyong Fu overall

1. Mohammad Rostami
2. Ziming Zhang
3. Soravit Changpinyo
4. Shafin Rahman
5. Wei-Lun Chao
6. Yanwei Fu
7. Venkatesh Saligrama
8. Jun Shu
9. Soheil Kolouri
10. Guosen Xie

Papers from Zhenyong Fu's perspective

Ordered by how strongly the researchers Zhenyong Fu 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. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Unsupervised Domain Adaptation for Zero-Shot Learning (2015) — 400 citations
• Transductive Multi-view Embedding for Zero-Shot Recognition and Annotation (2014) — 250 citations