Bo Zhao

Computer Vision and Pattern Recognition · with Feng · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 511 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 92 citations into it; #18,654 of 21,575 by trust here, #9,722 by citations
• Artificial Intelligence — 47 citations into it; #34,005 of 35,345 by trust here, #18,186 by citations
• Model Architectures — 15 citations into it
• Representation & Self-Supervised Learning — 7 citations into it
• Ecology — 5 citations into it
• Molecular Biology — 5 citations into it

Whom Bo Zhao trusts overall

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

1. Ross B. Girshick
2. Karen Simonyan
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Andrew Zisserman
6. Ilya Sutskever
7. Yann LeCun
8. Kaiming He
9. Yoshua Bengio
10. Christian Szegedy

Who trusts Bo Zhao overall

1. Yuxin Peng
2. Jianlong Fu
3. Xiren Ma
4. Heliang Zheng
5. Yue Chen
6. Ming Sun
7. Ze Yang
8. Zhongzhan Huang
9. Lipeng Ke
10. Tianshui Chen

Papers from Bo Zhao's perspective

Ordered by how strongly the researchers Bo Zhao 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. ImageNet: A large-scale hierarchical image database
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Diversified Visual Attention Networks for Fine-Grained Object Classification (2016) — 381 citations
• A survey on deep learning-based fine-grained object classification and semantic segmentation (2017) — 307 citations