Qingchen Zhang

Artificial Intelligence · 2016–2021

A researcher in the Science corpus: 4 papers; trusts 61 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 90 citations into it; #19,653 of 35,345 by trust here, #13,962 by citations
• Computer Vision and Pattern Recognition — 72 citations into it
• Model Architectures — 27 citations into it
• Representation & Self-Supervised Learning — 20 citations into it
• Optimization & Training — 14 citations into it
• Information Systems — 8 citations into it
• Management Science and Operations Research — 7 citations into it
• Privacy & Security — 7 citations into it

Whom Qingchen Zhang trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Pascal Vincent
4. Craig Gentry
5. Alex Krizhevsky
6. Yann LeCun
7. Jaideep Vaidya
8. Ruslan Salakhutdinov
9. Andrew Y. Ng
10. David E. Rumelhart

Who trusts Qingchen Zhang overall

1. Ahmed El Ouadrhiri
2. Ehsan Hesamifard
3. Qinbin Li
4. Ping Li
5. Bomin Mao
6. Javed Asharf
7. Billy Pik Lik Lau
8. Ahmed M Abdelhadi
9. Sweta Bhattacharya
10. Hassan Takabi

Papers from Qingchen Zhang's perspective

Ordered by how strongly the researchers Qingchen Zhang 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Convolutional neural networks for medical image analysis: State-of-the-art, comparisons, improvement and perspectives (2021) — 369 citations
• A survey on deep learning for big data (2018) — 726 citations
• Deep Computation Model for Unsupervised Feature Learning on Big Data (2016) — 138 citations
• Privacy Preserving Deep Computation Model on Cloud for Big Data Feature Learning (2016) — 261 citations