Amy Jin

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Amy Jin trusts overall

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

  1. Ross B. Girshick
  2. Alex Krizhevsky
  3. Geoffrey E. Hinton
  4. Ilya Sutskever
  5. Karen Simonyan
  6. Kaiming He
  7. Jeff Donahue
  8. Olga Russakovsky
  9. Jia Deng
  10. Andrew Zisserman

Papers from Amy Jin's perspective

Ordered by how strongly the researchers Amy Jin 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. ImageNet Large Scale Visual Recognition Challenge
  4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  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. ImageNet: A large-scale hierarchical image database
  10. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

Their papers