Yongwon Cho

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Yongwon Cho trusts overall

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

  1. Xiao Han
  2. Individualized Treat
  3. Geoffrey E. Hinton
  4. Yoshua Bengio
  5. Alec Radford
  6. Alex Krizhevsky
  7. Ross B. Girshick
  8. Yann LeCun
  9. Olaf Ronneberger
  10. Kaiming He

Papers from Yongwon Cho's perspective

Ordered by how strongly the researchers Yongwon Cho 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. Gradient-based learning applied to document recognition
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. GENERATIVE ADVERSARIAL NETS
  6. ImageNet: A large-scale hierarchical image database
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Long Short-Term Memory
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers