Ki Sang Hong

Computer Vision and Pattern Recognition · 2014–2018

A researcher in the Science corpus: 3 papers; trusts 734 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 102 citations into it; #10,248 of 21,575 by trust here, #11,721 by citations
• Artificial Intelligence — 31 citations into it; #25,314 of 35,345 by trust here, #33,294 by citations
• Media Technology — 28 citations into it; #3,532 of 3,621 by trust here, #2,954 by citations
• Model Architectures — 15 citations into it
• Generative Models — 13 citations into it
• Aerospace Engineering — 11 citations into it
• Human-Computer Interaction — 11 citations into it
• Evaluation & Benchmarks — 8 citations into it

Whom Ki Sang Hong trusts overall

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

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

Who trusts Ki Sang Hong overall

1. Guillermo Garcia-Hernando
2. Hao Chen
3. Fahad Lateef
4. Tae-Kyun Kim

Papers from Ki Sang Hong's perspective

Ordered by how strongly the researchers Ki Sang Hong 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. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• SRFeat: Single Image Super-Resolution with Feature Discrimination (2018) — 187 citations
• RDFNet: RGB-D Multi-level Residual Feature Fusion for Indoor Semantic Segmentation (2017) — 335 citations
• Enhanced Sequence Matching for Action Recognition from 3D Skeletal Data (2014) — 15 citations