Min H. Kim

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Min H. Kim trusts

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

  1. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  2. Karen Simonyan (in Computer Vision and Pattern Recognition)
  3. Mário A. T. Figueiredo (in Computational Mechanics)
  4. Trevor Darrell (in Computer Vision and Pattern Recognition)
  5. David J. Brady (in Computational Mechanics)
  6. Jonathan Long (in Computer Vision and Pattern Recognition)
  7. José M. Bioucas-Dias (in Computational Mechanics)
  8. Evan Shelhamer (in Computer Vision and Pattern Recognition)
  9. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  10. Kaiming He (in Computer Vision and Pattern Recognition)

Papers from Min H. Kim's perspective

Ordered by how strongly the researchers Min H. Kim trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  2. Fully convolutional networks for semantic segmentation
  3. ImageNet classification with deep convolutional neural networks
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Gradient-based learning applied to document recognition
  6. TensorFlow: A system for large-scale machine learning
  7. DeepFace: Closing the Gap to Human-Level Performance in Face Verification
  8. Learning Multiple Layers of Features from Tiny Images
  9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  10. Going deeper with convolutions

Their papers