Bin Kang

Computer Vision and Pattern Recognition · with Ji · 2020

A researcher in the Science corpus: 1 paper; trusts 237 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 44 citations into it
• Artificial Intelligence — 28 citations into it
• Model Architectures — 12 citations into it

Whom Bin Kang trusts overall

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

1. Kaiming He
2. Karen Simonyan
3. Andrew Zisserman
4. Alex Krizhevsky
5. Geoffrey E. Hinton
6. Ross B. Girshick
7. Yann LeCun
8. Yoshua Bengio
9. Ilya Sutskever
10. Diederik P. Kingma

Papers from Bin Kang's perspective

Ordered by how strongly the researchers Bin Kang 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. ImageNet: A large-scale hierarchical image database
4. Long Short-Term Memory
5. Going deeper with convolutions
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. ImageNet Large Scale Visual Recognition Challenge
8. Gradient-based learning applied to document recognition
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• TEA: Temporal Excitation and Aggregation for Action Recognition (2020) — 566 citations