Ruth Schulz

Computer Vision and Pattern Recognition · 2015

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Ruth Schulz trusts

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

  1. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  2. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  3. Trevor Darrell (in Computer Vision and Pattern Recognition)
  4. Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)
  5. Piotr Doll'ar (in Computer Vision and Pattern Recognition)
  6. Ilya Sutskever (in Computer Vision and Pattern Recognition)
  7. Antonio Torralba (in Computer Vision and Pattern Recognition)
  8. Jeff Donahue (in Computer Vision and Pattern Recognition)
  9. Jitendra Malik (in Computer Vision and Pattern Recognition)
  10. C. Lawrence Zitnick (in Computer Vision and Pattern Recognition)

Papers from Ruth Schulz's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. ImageNet Large Scale Visual Recognition Challenge
  3. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
  4. Backpropagation Applied to Handwritten Zip Code Recognition
  5. DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
  6. OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
  7. Caffe: Convolutional Architecture for Fast Feature Embedding
  8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  9. CNN Features Off-the-Shelf: An Astounding Baseline for Recognition
  10. Improving neural networks by preventing co-adaptation of feature detectors

Their papers