Takahiko Furuya

Computer Vision and Pattern Recognition · 2008–2015

A researcher in the Science corpus: 5 papers; trusts 31 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Takahiko Furuya trusts overall

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

  1. David G. Lowe
  2. Dietmar Saupe
  3. Josef Sivic
  4. M. Kazhdan
  5. Andrew Zisserman
  6. Rob Fergus
  7. Ran Gal
  8. Varun Jain

Papers from Takahiko Furuya's perspective

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

  1. Distinctive Image Features from Scale-Invariant Keypoints
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. ImageNet classification with deep convolutional neural networks
  4. ImageNet: A large-scale hierarchical image database
  5. Gradient-based learning applied to document recognition
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. ImageNet Large Scale Visual Recognition Challenge
  8. Going deeper with convolutions
  9. Long Short-Term Memory
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers