Seong-heum Kim

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 60 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Seong-heum Kim trusts overall

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

  1. David G. Lowe
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Ross B. Girshick
  5. Alex Krizhevsky
  6. Vinod Nair
  7. Hao Su
  8. Karen Simonyan
  9. Ilya Sutskever
  10. Yann LeCun

Papers from Seong-heum Kim's perspective

Ordered by how strongly the researchers Seong-heum 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. ImageNet: A large-scale hierarchical image database
  5. Gradient-based learning applied to document recognition
  6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  7. Long Short-Term Memory
  8. Attention is All you Need (Neural Information Processing Systems)
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers