Qin Han

IEEE International Conference on Computer Vision · 2022

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

Whom Qin Han trusts overall

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

  1. S. M. Seitz
  2. Adrian Broadhurst

Papers from Qin Han's perspective

Ordered by how strongly the researchers Qin Han 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. GENERATIVE ADVERSARIAL NETS
  6. ImageNet: A large-scale hierarchical image database
  7. Gradient-based learning applied to document recognition
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Long Short-Term Memory
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers