Heesung Kwon

Computer Vision and Pattern Recognition · 2005–2017

A researcher in the Science corpus: 3 papers; trusts 500 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 44 citations into it; #6,940 of 21,575 by trust here, #13,269 by citations
• Artificial Intelligence — 18 citations into it
• Media Technology — 14 citations into it; #719 of 3,621 by trust here, #1,365 by citations
• Model Architectures — 9 citations into it
• Atmospheric Science — 7 citations into it

Whom Heesung Kwon trusts overall

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

1. Bernhard Schölkopf
2. Kaiming He
3. Alex Krizhevsky
4. Ross B. Girshick
5. Geoffrey E. Hinton
6. Francis R. Bach
7. Yann LeCun
8. Mark A. Girolami
9. Karen Simonyan
10. Ilya Sutskever

Who trusts Heesung Kwon overall

1. Yang Xu
2. Xudong Kang
3. Telmo Adão
4. Shutao Li
5. Mengmeng Zhang
6. Huili Huang
7. Ava Vali
8. Nicolas Audebert
9. Swalpa Kumar Roy
10. Shifeng Zhang

Papers from Heesung Kwon's perspective

Ordered by how strongly the researchers Heesung Kwon 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. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• ME R-CNN: Multi-Expert Region-based CNN for Object Detection (2017) — 18 citations
• Kernel RX-algorithm: a nonlinear anomaly detector for hyperspectral imagery (2005) — 804 citations
• Going Deeper With Contextual CNN for Hyperspectral Image Classification (2016) — 930 citations