Julia Anne Schnabel

Computer Vision and Pattern Recognition · 2001–2023

A researcher in the Science corpus: 12 papers; trusts 96 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

Whom Julia Anne Schnabel trusts overall

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

  1. Daniel Rueckert
  2. Diederik P. Kingma
  3. Alex Krizhevsky
  4. Karen Simonyan
  5. Kaiming He
  6. Geoffrey E. Hinton
  7. Yoshua Bengio
  8. Paul J. Werbos
  9. Ilya Sutskever
  10. Pedro F. Felzenszwalb

Who trusts Julia Anne Schnabel overall

  1. Torsten Rohlfing
  2. Francisco P. M. Oliveira
  3. Mark Holden
  4. Daniel Rueckert
  5. Alejandro F Frangi
  6. Aristeidis Sotiras
  7. Siqi Liu
  8. João Manuel Ribeiro da Silva Tavares
  9. Xiahai Zhuang
  10. András P. Keszei

Papers from Julia Anne Schnabel's perspective

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

Their papers