G. M. Shaker

Computer Vision and Pattern Recognition · 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 G. M. Shaker trusts overall

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

  1. Jianchao Yang
  2. Alessandro Foi
  3. Lei Zhang
  4. John Wright
  5. Michael Elad
  6. Vladimir Katkovnik
  7. Weisheng Dong
  8. Thomas S. Huang
  9. E.J. Candes
  10. Michal Aharon

Papers from G. M. Shaker's perspective

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

Their papers