Benjamin Ummenhofer

Computer Vision and Pattern Recognition · 2015–2020

A researcher in the Science corpus: 3 papers; trusts 111 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

Whom Benjamin Ummenhofer trusts overall

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

  1. Diederik P. Kingma
  2. Brian Curless
  3. Geoffrey E. Hinton
  4. Yann LeCun
  5. Jimmy Ba
  6. Alex Krizhevsky
  7. M. Kazhdan
  8. Kaiming He
  9. Yoshua Bengio
  10. David Eigen

Who trusts Benjamin Ummenhofer overall

  1. Shuhao Cao
  2. Lequan Yu
  3. Zachary Teed
  4. Ibraheem Alhashim
  5. Philipp Holl
  6. Peter Hedman
  7. He Zhang
  8. Junhwa Hur
  9. Chengzhou Tang
  10. Rohan Chabra

Papers from Benjamin Ummenhofer's perspective

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

Their papers