Li Tong

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 49 citations into it
• Computer Vision and Pattern Recognition — 43 citations into it
• Radiology, Nuclear Medicine and Imaging — 25 citations into it
• Representation & Self-Supervised Learning — 13 citations into it
• Molecular Biology — 8 citations into it

Whom Li Tong trusts overall

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

1. Gabriella Csurka
2. Sergey Ioffe
3. Geoffrey E. Hinton
4. Christian Szegedy
5. Alex Krizhevsky
6. Chris H. Q. Ding
7. Eric Tzeng
8. Yoshua Bengio
9. Kaiming He
10. Yann LeCun

Who trusts Li Tong overall

1. Samuel Budd
2. Fei Zhao

Papers from Li Tong's perspective

Ordered by how strongly the researchers Li Tong 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. Gradient-based learning applied to document recognition
4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. ImageNet Large Scale Visual Recognition Challenge
8. Long Short-Term Memory
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Multimodal deep learning models for early detection of Alzheimer’s disease stage (2021) — 653 citations
• Advancing Medical Imaging Informatics by Deep Learning-Based Domain Adaptation (2020) — 79 citations