Jamie Yeung

Computer Vision and Pattern Recognition · 2015

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 Jamie Yeung trusts

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

  1. Peter J. Green (in Probabilistic & Bayesian Methods)
  2. Jitendra Malik (in Computer Vision and Pattern Recognition)
  3. David G. Lowe (in Computer Vision and Pattern Recognition)
  4. Pablo Arbeláez (in Computer Vision and Pattern Recognition)

Papers from Jamie Yeung's perspective

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

  1. Distinctive Image Features from Scale-Invariant Keypoints
  2. Indoor Segmentation and Support Inference from RGBD Images
  3. ImageNet classification with deep convolutional neural networks
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Multiple View Geometry in Computer Vision
  6. Gradient-based learning applied to document recognition
  7. Fast approximate energy minimization via graph cuts
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. ImageNet: A large-scale hierarchical image database
  10. Going deeper with convolutions

Their papers