Koichi Ito

Computer Vision and Pattern Recognition · with Biljecki · 2021

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Koichi Ito trusts overall

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

  1. Liang-Chieh Chen
  2. Gerhard Neuhold
  3. Yao Yao
  4. Marius Cordts

Papers from Koichi Ito's perspective

Ordered by how strongly the researchers Koichi 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 classification with deep convolutional neural networks
  3. ImageNet: A large-scale hierarchical image database
  4. ImageNet Large Scale Visual Recognition Challenge
  5. Gradient-based learning applied to document recognition
  6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  8. The Cityscapes Dataset for Semantic Urban Scene Understanding
  9. Going deeper with convolutions
  10. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

Their papers