Ming Zhong

Computer Vision and Pattern Recognition · with Chen · 2021

A researcher in the Science corpus: 1 paper; trusts 46 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Ming Zhong trusts overall

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

  1. Diederik P. Kingma
  2. Geoffrey E. Hinton
  3. Alex Krizhevsky
  4. Yoshua Bengio
  5. Kaiming He
  6. Ilya Sutskever
  7. Jimmy Ba
  8. Alec Radford
  9. Andrew Zisserman
  10. Yann LeCun

Papers from Ming Zhong's perspective

Ordered by how strongly the researchers Ming Zhong 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  6. ImageNet: A large-scale hierarchical image database
  7. Gradient-based learning applied to document recognition
  8. ImageNet Large Scale Visual Recognition Challenge
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Going deeper with convolutions

Their papers