Tae-Hyun Oh

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 7 papers; trusts 1,085 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

Whom Tae-Hyun Oh trusts overall

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

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

Who trusts Tae-Hyun Oh overall

  1. Zejia Weng
  2. Ruohan Gao
  3. Rameswar Panda
  4. Mandela Patrick
  5. Hengduo Li
  6. Zuxuan Wu
  7. Haytham M. Fayek
  8. Kristen Grauman
  9. Amir Ghodrati
  10. Soo-Whan Chung

Papers from Tae-Hyun Oh's perspective

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

Their papers