Youngeun Kim

Computer Vision and Pattern Recognition · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 69 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Youngeun Kim trusts overall

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

  1. Kaiming He
  2. Diederik P. Kingma
  3. Mang Ye
  4. Geoffrey E. Hinton
  5. Alex Krizhevsky
  6. Navneet Dalal
  7. Jia Deng
  8. Yoshua Bengio
  9. Yifan Sun
  10. Jimmy Ba

Papers from Youngeun Kim's perspective

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

Their papers