Nico Hoffmann

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 96 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Nico Hoffmann trusts overall

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

  1. Alex Krizhevsky
  2. Kaiming He
  3. Ross B. Girshick
  4. Geoffrey E. Hinton
  5. Jia Deng
  6. Evan Shelhamer
  7. X. Zhang
  8. Yann LeCun
  9. Trevor Darrell
  10. Yoshua Bengio

Papers from Nico Hoffmann's perspective

Ordered by how strongly the researchers Nico Hoffmann trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. ImageNet classification with deep convolutional neural networks
  3. ImageNet: A large-scale hierarchical image database
  4. Learning Multiple Layers of Features from Tiny Images
  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. Attention is All you Need (Neural Information Processing Systems)
  9. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
  10. Going deeper with convolutions

Their papers