Philipp Seegerer

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Philipp Seegerer trusts overall

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

  1. Karen Simonyan
  2. Matthew D. Zeiler
  3. Geoffrey E. Hinton
  4. Alex Krizhevsky
  5. Andrew Zisserman
  6. Yann LeCun

Who trusts Philipp Seegerer overall

  1. Wojciech Samek

Papers from Philipp Seegerer's perspective

Ordered by how strongly the researchers Philipp Seegerer 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. ImageNet: A large-scale hierarchical image database
  4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  5. Gradient-based learning applied to document recognition
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Long Short-Term Memory
  8. ImageNet Large Scale Visual Recognition Challenge
  9. Learning Multiple Layers of Features from Tiny Images
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers