Justin Carpentier

Computer Vision and Pattern Recognition · 2019–2020

A researcher in the Science corpus: 3 papers; trusts 132 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Justin Carpentier trusts overall

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

  1. David G. Lowe
  2. Diederik P. Kingma
  3. Kaiming He
  4. Ross B. Girshick
  5. Geoffrey E. Hinton
  6. Navneet Dalal
  7. Alex Krizhevsky
  8. Andrew Zisserman
  9. Shaoqing Ren
  10. Johannes L. Schönberger

Who trusts Justin Carpentier overall

  1. Carlos Mastalli

Papers from Justin Carpentier's perspective

Ordered by how strongly the researchers Justin Carpentier 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. 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. Long Short-Term Memory
  7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  8. Attention is All you Need (Neural Information Processing Systems)
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Going deeper with convolutions

Their papers