Kevin M. Cherry

Computer Vision and Pattern Recognition · 2014–2018

A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Kevin M. Cherry trusts overall

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

  1. Alex Krizhevsky
  2. Matthew D. Zeiler
  3. Geoffrey E. Hinton
  4. David Y. Zhang
  5. Yann LeCun
  6. Ilya Sutskever
  7. Rob Fergus
  8. Li Deng
  9. John J. Hopfield

Who trusts Kevin M. Cherry overall

  1. Kenji Suzuki
  2. Le Lu

Papers from Kevin M. Cherry's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  3. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
  4. Gradient-based learning applied to document recognition
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Dropout: a simple way to prevent neural networks from overfitting
  7. Backpropagation Applied to Handwritten Zip Code Recognition
  8. Long Short-Term Memory
  9. Learning Multiple Layers of Features from Tiny Images
  10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers