Yingkun Hou

Computer Vision and Pattern Recognition · 2014–2019

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Yingkun Hou trusts overall

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

  1. Michael Lustig
  2. Xueyang Fu
  3. Gitta Kutyniok
  4. Hamid R. Sheikh
  5. Yu Li
  6. E.J. Candes
  7. A. Bovik
  8. Junfeng Yang
  9. Carlo Tomasi
  10. Joshua D. Trzasko

Who trusts Yingkun Hou overall

  1. Yan Yang

Papers from Yingkun Hou's perspective

Ordered by how strongly the researchers Yingkun Hou 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. Gradient-based learning applied to document recognition
  5. ImageNet: A large-scale hierarchical image database
  6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Image quality assessment: from error visibility to structural similarity
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers