Olga Saukh

Computer Vision and Pattern Recognition · 2011–2023

A researcher in the Science corpus: 4 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Olga Saukh trusts

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

  1. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  2. Kaiming He (in Computer Vision and Pattern Recognition)
  3. Karen Simonyan (in Computer Vision and Pattern Recognition)
  4. Shaoqing Ren (in Computer Vision and Pattern Recognition)
  5. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  6. Li Fei-Fei (in Computer Vision and Pattern Recognition)
  7. X. Zhang (in Computer Vision and Pattern Recognition)

Papers from Olga Saukh's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. ImageNet classification with deep convolutional neural networks
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. ImageNet: A large-scale hierarchical image database
  5. ImageNet Large Scale Visual Recognition Challenge
  6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  7. Gradient-based learning applied to document recognition
  8. Learning Multiple Layers of Features from Tiny Images
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Language Models are Few-Shot Learners (Neural Information Processing Systems)

Their papers