Hideaki Suzuki

Computer Vision and Pattern Recognition · 2017

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

Subfields

Whom Hideaki Suzuki 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)

Papers from Hideaki Suzuki's perspective

Ordered by how strongly the researchers Hideaki Suzuki 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  5. Fully convolutional networks for semantic segmentation
  6. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  7. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
  8. ImageNet classification with deep convolutional neural networks
  9. Gradient-based learning applied to document recognition
  10. How transferable are features in deep neural networks?

Their papers