Hitoshi Habe

Computer Vision and Pattern Recognition · 2012

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Hitoshi Habe trusts overall

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

  1. Leo Breiman
  2. Jamie Shotton
  3. Antonio Criminisi
  4. Tin Kam Ho
  5. Yoav Freund
  6. Vincent Lepetit

Papers from Hitoshi Habe's perspective

Ordered by how strongly the researchers Hitoshi Habe 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  5. Gradient-based learning applied to document recognition
  6. Distinctive Image Features from Scale-Invariant Keypoints
  7. Going deeper with convolutions
  8. Histograms of oriented gradients for human detection
  9. ImageNet Large Scale Visual Recognition Challenge
  10. ImageNet: A large-scale hierarchical image database

Their papers