Myung-joo Kang

Computer Vision and Pattern Recognition · 2000–2021

A researcher in the Science corpus: 7 papers; trusts 27 researchers and is trusted by 58 researchers here, as inferred from the citation graph.

Subfields

Whom Myung-joo Kang trusts overall

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

  1. Xu-Dong Liu
  2. Ronald Fedkiw
  3. Stanley J. Osher
  4. James A. Sethian
  5. Tero Karras
  6. Diederik P. Kingma

Who trusts Myung-joo Kang overall

  1. Zhilin Li
  2. Ronald Fedkiw
  3. Frédéric Gibou
  4. Frank Losasso
  5. Gihun Son
  6. Douglas Enright
  7. Duc Quang Nguyen
  8. W. Tan
  9. Stanley J. Osher
  10. Mark Sussman

Papers from Myung-joo Kang's perspective

Ordered by how strongly the researchers Myung-joo Kang trusts endorse each paper. Same corpus, a different order for every researcher.

  1. GENERATIVE ADVERSARIAL NETS
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. ImageNet classification with deep convolutional neural networks
  4. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
  5. Rectified Linear Units Improve Restricted Boltzmann Machines
  6. Gradient-based learning applied to document recognition
  7. GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
  8. Learning Transferable Visual Models From Natural Language Supervision (International Conference on Machine Learning)
  9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers