Jungseok Hong

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 250 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Jungseok Hong trusts overall

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

  1. Kaiming He
  2. Ross B. Girshick
  3. Shaoqing Ren
  4. Deborah A. Maranville
  5. Geoffrey E. Hinton
  6. Christian Szegedy
  7. Alex Krizhevsky
  8. Karen Simonyan
  9. Michael Fulton
  10. Diederik P. Kingma

Who trusts Jungseok Hong overall

  1. Michael Fulton
  2. Junaed Sattar
  3. Alexander Kirillov

Papers from Jungseok Hong's perspective

Ordered by how strongly the researchers Jungseok 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. Gradient-based learning applied to document recognition
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Long Short-Term Memory
  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