Fa-Ting Hong

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 161 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it; #29,131 of 35,345 by trust here, #34,213 by citations
• Computer Vision and Pattern Recognition — 21 citations into it
• Representation & Self-Supervised Learning — 6 citations into it
• Computer Networks and Communications — 5 citations into it; #7,994 of 9,886 by trust here, #9,518 by citations

Whom Fa-Ting Hong trusts overall

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

1. Geoffrey E. Hinton
2. João Carreira
3. Dong-Hyun Lee
4. Andrew Zisserman
5. Alex Krizhevsky
6. Yoshua Bengio
7. Yang Zou
8. Kaiming He
9. L. V. D. van der Maaten
10. Karen Simonyan

Who trusts Fa-Ting Hong overall

1. Sijie Li

Papers from Fa-Ting Hong's perspective

Ordered by how strongly the researchers Fa-Ting Hong 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
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

• MIST: Multiple Instance Self-Training Framework for Video Anomaly Detection (2021) — 368 citations