Horst-Michael Groß

Computer Vision and Pattern Recognition · 2014–2020

A researcher in the Science corpus: 5 papers; trusts 374 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Horst-Michael Groß trusts overall

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

  1. Ross B. Girshick
  2. Kaiming He
  3. Bo Li
  4. Geoffrey E. Hinton
  5. Alex Krizhevsky
  6. Shaoqing Ren
  7. Diederik P. Kingma
  8. Karen Simonyan
  9. Yann LeCun
  10. Yoshua Bengio

Who trusts Horst-Michael Groß overall

  1. Eduardo Arnold

Papers from Horst-Michael Groß's perspective

Ordered by how strongly the researchers Horst-Michael Groß 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  5. ImageNet: A large-scale hierarchical image database
  6. Gradient-based learning applied to document recognition
  7. Long Short-Term Memory
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers