Jonathan Prescott-Roy

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jonathan Prescott-Roy trusts

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

  1. Kaiming He (in Computer Vision and Pattern Recognition)
  2. Shaoqing Ren (in Computer Vision and Pattern Recognition)
  3. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  4. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  5. X. Zhang (in Computer Vision and Pattern Recognition)
  6. Karen Simonyan (in Computer Vision and Pattern Recognition)
  7. Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)
  8. Ilya Sutskever (in Computer Vision and Pattern Recognition)
  9. James J. DiCarlo (in Cognitive Neuroscience)
  10. Ross B. Girshick (in Computer Vision and Pattern Recognition)

Papers from Jonathan Prescott-Roy's perspective

Ordered by how strongly the researchers Jonathan Prescott-Roy 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: A large-scale hierarchical image database
  3. Going deeper with convolutions
  4. ImageNet Large Scale Visual Recognition Challenge
  5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  7. Microsoft COCO: Common Objects in Context
  8. Densely Connected Convolutional Networks
  9. Understanding the difficulty of training deep feedforward neural networks
  10. ImageNet classification with deep convolutional neural networks

Their papers