Thanh Thi Nguyen

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 6 papers; trusts 472 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 160 citations into it
• Artificial Intelligence — 147 citations into it; #20,238 of 35,345 by trust here, #18,586 by citations
• Reinforcement Learning — 93 citations into it
• Generative Models — 43 citations into it
• Computer Networks and Communications — 31 citations into it
• Control and Systems Engineering — 27 citations into it
• Signal Processing — 27 citations into it
• Electrical and Electronic Engineering — 24 citations into it

Whom Thanh Thi Nguyen trusts overall

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

1. Richard S. Sutton
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Kaiming He
6. Yoshua Bengio
7. Karen Simonyan
8. Volodymyr Mnih
9. Ronald J. Williams
10. Yann LeCun

Who trusts Thanh Thi Nguyen overall

1. Jieyi Long
2. Amal Feriani
3. Vijay Janappa Reddi
4. Michele Polese
5. Deressa Wodajo
6. Chao Yu
7. Roxana Rădulescu
8. Ekram Hossain
9. Momina Masood
10. Solomon Atnafu

Papers from Thanh Thi Nguyen's perspective

Ordered by how strongly the researchers Thanh Thi Nguyen 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
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

• Deep learning for deepfakes creation and detection: A survey (2019) — 629 citations
• Deep Reinforcement Learning for Multiagent Systems: A Review of Challenges, Solutions, and Applications (2018) — 1,032 citations
• A New Tensioning Method using Deep Reinforcement Learning for Surgical Pattern Cutting (2019) — 42 citations
• Deep Reinforcement Learning for Cyber Security (2019) — 542 citations
• Deep Learning for Deepfakes Creation and Detection (2019) — 150 citations
• Extreme learning machine based transfer learning algorithms: A survey (2017) — 79 citations