Peter Nakaji

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 3 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Peter Nakaji trusts

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

  1. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  2. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  3. Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)
  4. Ilya Sutskever (in Computer Vision and Pattern Recognition)
  5. Antonio Torralba (in Computer Vision and Pattern Recognition)
  6. Karen Simonyan (in Computer Vision and Pattern Recognition)
  7. Cordelia Schmid (in Computer Vision and Pattern Recognition)
  8. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  9. Aude Oliva (in Computer Vision and Pattern Recognition)
  10. Andrea Vedaldi (in Computer Vision and Pattern Recognition)

Papers from Peter Nakaji's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Going deeper with convolutions
  3. Rethinking the Inception Architecture for Computer Vision
  4. Caffe: Convolutional Architecture for Fast Feature Embedding
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Gradient-based learning applied to document recognition
  7. Learning representations by back-propagating errors
  8. Long Short-Term Memory
  9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  10. Learning Multiple Layers of Features from Tiny Images

Their papers