Michael Tsang

Computer Vision and Pattern Recognition · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 54 citations into it

Whom Michael Tsang trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Kaiming He
4. Christian Szegedy
5. Diederik P. Kingma
6. Huy Hoang Le Nguyen
7. Oscar Li
8. Yoshua Bengio
9. Karen Simonyan
10. Justus Thies

Papers from Michael Tsang's perspective

Ordered by how strongly the researchers Michael Tsang 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Going deeper with convolutions
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• DHEN: A Deep and Hierarchical Ensemble Network for Large-Scale Click-Through Rate Prediction (2022) — 17 citations
• Interpretable and Trustworthy Deepfake Detection via Dynamic Prototypes (2021) — 101 citations