Jin-Hwan Kim

Computer Vision and Pattern Recognition · with Jang · 2013

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 Jin-Hwan Kim trusts overall

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

  1. Raanan Fattal
  2. Richard Szeliski
  3. Kaiming He
  4. Jean-Philippe Tarel
  5. Takeo Kanade
  6. Xiaoou Tang
  7. Nicolas Hautière
  8. Robby T. Tan
  9. Srinivasa G. Narasimhan
  10. Yoav Y. Schechner

Papers from Jin-Hwan Kim's perspective

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

Their papers