Kiho Hong

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 277 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 32 citations into it; #12,421 of 21,575 by trust here, #16,787 by citations
• Artificial Intelligence — 21 citations into it
• Optimization & Training — 10 citations into it
• Model Architectures — 7 citations into it
• Efficiency & Compression — 6 citations into it

Whom Kiho Hong trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Kaiming He
4. Andrew Zisserman
5. Yoshua Bengio
6. Christian Szegedy
7. Ilya Sutskever
8. Quoc V. Le
9. Ross B. Girshick
10. Yann LeCun

Who trusts Kiho Hong overall

1. Tal Ridnik

Papers from Kiho Hong's perspective

Ordered by how strongly the researchers Kiho Hong trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. ImageNet Large Scale Visual Recognition Challenge
6. Long Short-Term Memory
7. Going deeper with convolutions
8. Gradient-based learning applied to document recognition
9. Attention is All you Need (Neural Information Processing Systems)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network (2020) — 58 citations