Seokil Hong

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 2 papers; trusts 68 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Seokil Hong trusts overall

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

  1. Ian J. Goodfellow
  2. Geoffrey E. Hinton
  3. Radu Timofte
  4. Yoshua Bengio
  5. Alex Krizhevsky
  6. R. M. French
  7. Yann LeCun
  8. Diederik P. Kingma
  9. Kaiming He
  10. Ilya Sutskever

Who trusts Seokil Hong overall

  1. Dong Yin
  2. Liangzu Peng
  3. Mozhgan Pourkeshavarz
  4. Kelvin C. K. Chan
  5. Shixiang Tang

Papers from Seokil Hong's perspective

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

Their papers