Peter R. Innocent

International Journal of Computer Vision · 2002

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Whom Peter R. Innocent trusts overall

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

  1. Bill Triggs

Who trusts Peter R. Innocent overall

  1. Heiko Hirschmüller
  2. Daniel Scharstein
  3. Ruigang Yang
  4. Haofei Xu
  5. Sunok Kim

Papers from Peter R. Innocent's perspective

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

  1. Vision Algorithms: Theory and Practice (Lecture Notes in Computer Science)
  2. Distinctive Image Features from Scale-Invariant Keypoints
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Histograms of oriented gradients for human detection
  5. ImageNet classification with deep convolutional neural networks
  6. Gradient-based learning applied to document recognition
  7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  8. Object recognition from local scale-invariant features
  9. Going deeper with convolutions
  10. Long Short-Term Memory

Their papers