Stefan Müller

Computer Vision and Pattern Recognition · with Bernuth · 2019

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Stefan Müller trusts overall

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

  1. Joseph Redmon
  2. Ross B. Girshick
  3. Kaiming He
  4. Shaoqing Ren
  5. Samuel F. Dodge
  6. Tsung-Yi Lin
  7. Mark Everingham
  8. Geoffrey E. Hinton
  9. Alex Krizhevsky
  10. Anurag Arnab

Papers from Stefan Müller's perspective

Ordered by how strongly the researchers Stefan Müller 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. ImageNet Large Scale Visual Recognition Challenge
  7. Long Short-Term Memory
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Microsoft COCO: Common Objects in Context
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers