Fanjie Kong
Computer Vision and Pattern Recognition · 2020–2021
A researcher in the Science corpus: 3 papers; trusts 335 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 70 citations into it
- Artificial Intelligence — 64 citations into it
- Representation & Self-Supervised Learning — 13 citations into it
- Model Architectures — 8 citations into it
- Optimization & Training — 7 citations into it
- Efficiency & Compression — 6 citations into it
Whom Fanjie Kong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Kaiming He
- Alex Krizhevsky
- Hugo Larochelle
- Yoshua Bengio
- Yann LeCun
- Ilya Sutskever
- Ross B. Girshick
- Diederik P. Kingma
- Andrew Zisserman
Who trusts Fanjie Kong overall
Papers from Fanjie Kong's perspective
Ordered by how strongly the researchers Fanjie Kong trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Efficient Classification of Very Large Images with Tiny Objects (2021) — 38 citations
- Quantum Tensor Network in Machine Learning: An Application to Tiny Object Classification (2021) — 14 citations
- Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models (2020) — 17 citations