Yun Ye

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Yun Ye trusts overall

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

  1. Kaiming He
  2. Jiankang Deng
  3. Alex Krizhevsky
  4. Geoffrey E. Hinton
  5. Ross B. Girshick

Papers from Yun Ye's perspective

Ordered by how strongly the researchers Yun Ye 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. Going deeper with convolutions
  4. ImageNet Large Scale Visual Recognition Challenge
  5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  7. Gradient-based learning applied to document recognition
  8. ImageNet: A large-scale hierarchical image database
  9. Dropout: a simple way to prevent neural networks from overfitting
  10. Long Short-Term Memory

Their papers