Kotaro Ito

Artificial Intelligence · 2018

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 Kotaro Ito trusts

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

  1. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  2. Karen Simonyan (in Computer Vision and Pattern Recognition)
  3. Francis R. Bach (in Artificial Intelligence)

Papers from Kotaro Ito's perspective

Ordered by how strongly the researchers Kotaro Ito 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: A large-scale hierarchical image database
  3. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  4. ImageNet classification with deep convolutional neural networks
  5. Gradient-based learning applied to document recognition
  6. Rectified Linear Units Improve Restricted Boltzmann Machines
  7. Densely Connected Convolutional Networks
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. Learning Multiple Layers of Features from Tiny Images
  10. Long Short-Term Memory

Their papers