Thomas B. Preußer

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Thomas B. Preußer trusts overall

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

  1. Alex Krizhevsky
  2. Geoffrey E. Hinton
  3. Yann LeCun
  4. Song Han
  5. Ilya Sutskever
  6. Yoshua Bengio
  7. Karen Simonyan
  8. Kaiming He
  9. Janardan Misra
  10. Zhaowei Cai

Papers from Thomas B. Preußer's perspective

Ordered by how strongly the researchers Thomas B. Preußer 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  4. Gradient-based learning applied to document recognition
  5. Long Short-Term Memory
  6. ImageNet: A large-scale hierarchical image database
  7. Going deeper with convolutions
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  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