Zeng-Huang Hou

Computer Vision and Pattern Recognition · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 204 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Zeng-Huang Hou trusts overall

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

  1. Kaiming He
  2. Geoffrey E. Hinton
  3. Alex Krizhevsky
  4. Liang Zheng
  5. Navneet Dalal
  6. Ross B. Girshick
  7. Yoshua Bengio
  8. Diederik P. Kingma
  9. Yann LeCun
  10. Xiatian Zhu

Papers from Zeng-Huang Hou's perspective

Ordered by how strongly the researchers Zeng-Huang Hou 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. ImageNet Large Scale Visual Recognition Challenge
  4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  5. ImageNet: A large-scale hierarchical image database
  6. Gradient-based learning applied to document recognition
  7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  8. GENERATIVE ADVERSARIAL NETS
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Long Short-Term Memory

Their papers