Michael Blot

Computer Vision and Pattern Recognition · 2016

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Michael Blot trusts overall

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

  1. Stephen P. Boyd
  2. Alex Krizhevsky
  3. Kaiming He
  4. Yann LeCun
  5. Sixin Zhang
  6. David Kempe
  7. Igor Colin
  8. Geoffrey E. Hinton
  9. X. Zhang
  10. Anna Choromanska

Who trusts Michael Blot overall

  1. Stefano Savazzi
  2. Yuanming Shi
  3. Zhi Zhou
  4. Monica Nicoli
  5. Kai Yang

Papers from Michael Blot's perspective

Ordered by how strongly the researchers Michael Blot 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. Learning Multiple Layers of Features from Tiny Images
  5. ImageNet Large Scale Visual Recognition Challenge
  6. ImageNet: A large-scale hierarchical image database
  7. Long Short-Term Memory
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers