I. Park

Computer Vision and Pattern Recognition · with Chang · 2018

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom I. Park trusts

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

  1. Karen Simonyan (in Computer Vision and Pattern Recognition)
  2. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  3. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  4. Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)

Papers from I. Park's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Gradient-based learning applied to document recognition
  3. ImageNet Large Scale Visual Recognition Challenge
  4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  6. Dropout: a simple way to prevent neural networks from overfitting
  7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  8. Long Short-Term Memory
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Learning Multiple Layers of Features from Tiny Images

Their papers