N. Yamazaki

Computer Vision and Pattern Recognition · 2017–2022

A researcher in the Science corpus: 5 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom N. Yamazaki trusts overall

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

  1. Ning Qian
  2. Karen Simonyan
  3. Seiya Tokui

Papers from N. Yamazaki's perspective

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

  1. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  2. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
  3. ImageNet classification with deep convolutional neural networks
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Gradient-based learning applied to document recognition
  6. ImageNet: A large-scale hierarchical image database
  7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  8. ImageNet Large Scale Visual Recognition Challenge
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Long Short-Term Memory

Their papers