Simone Schaub-Meyer

Computer Vision and Pattern Recognition · 2015

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Simone Schaub-Meyer trusts overall

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

  1. Ce Liu
  2. Deqing Sun
  3. Li Xu
  4. Eero P. Simoncelli
  5. Neal Wadhwa
  6. William T. Freeman
  7. Stefan Roth
  8. Jiaya Jia
  9. Michael J. Black
  10. Michael Rubinstein

Who trusts Simone Schaub-Meyer overall

  1. Simon Niklaus
  2. Feng Liu
  3. Long Mai
  4. Wenbo Bao
  5. Myungsub Choi
  6. Richard Zhang
  7. Ziwei Liu
  8. Huaizu Jiang
  9. Jingwei Xu
  10. Wei-Sheng Lai

Papers from Simone Schaub-Meyer's perspective

Ordered by how strongly the researchers Simone Schaub-Meyer trusts endorse each paper. Same corpus, a different order for every researcher.

  1. ImageNet classification with deep convolutional neural networks
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. Gradient-based learning applied to document recognition
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. ImageNet: A large-scale hierarchical image database
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet Large Scale Visual Recognition Challenge
  8. Going deeper with convolutions
  9. Long Short-Term Memory
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers