Joachim Hornegger

Computer Vision and Pattern Recognition · 2009–2019

A researcher in the Science corpus: 11 papers; trusts 30 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Joachim Hornegger trusts overall

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

  1. John F. Canny
  2. Yoshua Bengio
  3. Radford M. Neal
  4. Yann LeCun
  5. Longxin Lin
  6. Geoffrey E. Hinton
  7. Bashir Al-Diri

Who trusts Joachim Hornegger overall

  1. José Ignacio Orlando

Papers from Joachim Hornegger's perspective

Ordered by how strongly the researchers Joachim Hornegger trusts endorse each paper. Same corpus, a different order for every researcher.

  1. ImageNet classification with deep convolutional neural networks
  2. Gradient-based learning applied to document recognition
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Fully convolutional networks for semantic segmentation
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  8. ImageNet: A large-scale hierarchical image database
  9. Learning Multiple Layers of Features from Tiny Images
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers