S. Cook

Computer Vision and Pattern Recognition · Genetics in Medicine · 2012–2019

A researcher in the Science corpus: 9 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom S. Cook trusts

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

  1. Andrew Zisserman (in Computer Vision and Pattern Recognition)

Papers from S. Cook's perspective

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

  1. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  2. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
  3. Fully convolutional networks for semantic segmentation
  4. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  5. Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
  6. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
  7. ImageNet classification with deep convolutional neural networks
  8. Perceptual Losses for Real-Time Style Transfer and Super-Resolution
  9. Image quality assessment: from error visibility to structural similarity
  10. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)

Their papers