Matthias Heiler

Computer Vision and Pattern Recognition · 2003

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

Whom Matthias Heiler trusts overall

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

  1. Song-Chun Zhu
  2. Stéphane Mallat

Who trusts Matthias Heiler overall

  1. Massimo Minervini
  2. Hanno Scharr
  3. Li Fei-Fei
  4. Andreas Fischbach
  5. Daniel Cremers
  6. Sotirios A. Tsaftaris
  7. R. VanRullen
  8. Erik B. Sudderth
  9. Sam Hallman
  10. Guillaume A. Rousselet

Papers from Matthias Heiler's perspective

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

Their papers