Boxin Shi

Computer Vision and Pattern Recognition · with Heng · 2020

A researcher in the Science corpus: 1 paper; trusts 70 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Boxin Shi trusts overall

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

  1. Simon Niklaus
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Sergey Ioffe
  5. Alex Krizhevsky
  6. Feng Liu
  7. Christian Szegedy
  8. Dong-Hyun Lee
  9. Diederik P. Kingma
  10. Yoshua Bengio

Papers from Boxin Shi's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Gradient-based learning applied to document recognition
  6. ImageNet: A large-scale hierarchical image database
  7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Learning Multiple Layers of Features from Tiny Images
  10. Going deeper with convolutions

Their papers