Tengfei Song

Experimental and Cognitive Psychology · 2019–2020

A researcher in the Science corpus: 3 papers; trusts 65 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Experimental and Cognitive Psychology — 39 citations into it; #9,407 of 9,731 by trust here, #4,714 by citations
• Computer Vision and Pattern Recognition — 31 citations into it
• Cognitive Neuroscience — 30 citations into it; #10,468 of 10,852 by trust here, #5,990 by citations
• Artificial Intelligence — 27 citations into it
• Signal Processing — 7 citations into it
• Computational Theory and Mathematics — 6 citations into it
• Graph Learning — 6 citations into it
• Cardiology and Cardiovascular Medicine — 5 citations into it

Whom Tengfei Song trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Kaiming He
4. Wei-Long Zheng
5. Ulrike von Luxburg
6. William Stafford Noble
7. Shlomo Hoory
8. A. Hinge
9. Ilya Sutskever
10. Vinod Nair

Who trusts Tengfei Song overall

1. Dongrui Wu
2. Peixiang Zhong
3. Wei-Bang Jiang
4. Nazmi Sofian Suhaimi
5. Yonghao Song
6. Wei Liu
7. Yang Li
8. Xiang Li
9. Xiaotong Gu
10. Wei Tao

Papers from Tengfei Song's perspective

Ordered by how strongly the researchers Tengfei Song 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. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
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

• Knowledge Augmented Deep Neural Networks for Joint Facial Expression and Action Unit Recognition (2020) — 68 citations
• EEG Emotion Recognition Using Dynamical Graph Convolutional Neural Networks (2020) — 1,382 citations
• A Novel Bi-Hemispheric Discrepancy Model for EEG Emotion Recognition (2019) — 325 citations