Takamasa Kudo

Computer Vision and Pattern Recognition · 2016–2019

A researcher in the Science corpus: 2 papers; trusts 47 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Takamasa Kudo trusts overall

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

  1. Kaiming He
  2. Geoffrey E. Hinton
  3. Alex Krizhevsky
  4. Ross B. Girshick
  5. Yoshua Bengio
  6. Yann LeCun
  7. Ilya Sutskever
  8. Diederik P. Kingma
  9. Christian Szegedy
  10. David E. Rumelhart

Who trusts Takamasa Kudo overall

  1. C. Stringer

Papers from Takamasa Kudo's perspective

Ordered by how strongly the researchers Takamasa Kudo 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. Gradient-based learning applied to document recognition
  5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  8. ImageNet: A large-scale hierarchical image database
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers