Sungheon Park

Computer Vision and Pattern Recognition · 2016

A researcher in the Science corpus: 2 papers; trusts 324 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 37 citations into it; #7,190 of 21,575 by trust here, #13,269 by citations
• Artificial Intelligence — 19 citations into it; #14,948 of 35,345 by trust here, #29,412 by citations
• Model Architectures — 12 citations into it
• Human-Computer Interaction — 7 citations into it; #816 of 2,253 by trust here, #1,332 by citations
• Optimization & Training — 7 citations into it; #1,404 of 2,601 by trust here, #2,313 by citations

Whom Sungheon Park trusts overall

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

1. Alex Krizhevsky
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Yann LeCun
5. Sergey Ioffe
6. Kaiming He
7. Christian Szegedy
8. Matthew D. Zeiler
9. Karen Simonyan
10. Ilya Sutskever

Who trusts Sungheon Park overall

1. Tao Hu
2. Terrance Devries
3. Junsuk Choe
4. Mir Rayat Imtiaz Hossain
5. Gyeongsik Moon
6. Grégory Rogez
7. Jun Liu
8. Xiao Sun
9. Bugra Tekin
10. Julieta Martinez

Papers from Sungheon Park's perspective

Ordered by how strongly the researchers Sungheon Park 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• 3D Human Pose Estimation Using Convolutional Neural Networks with 2D Pose Information (2016) — 172 citations
• Analysis on the Dropout Effect in Convolutional Neural Networks (2016) — 217 citations