Bin Fu

Computer Vision and Pattern Recognition · 2021–2024

A researcher in the Science corpus: 4 papers; trusts 260 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Bin Fu trusts overall

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

  1. Kaiming He
  2. Geoffrey E. Hinton
  3. Diederik P. Kingma
  4. Alex Krizhevsky
  5. Yoshua Bengio
  6. Ross B. Girshick
  7. Ilya Sutskever
  8. Yann LeCun
  9. Tsung-Yi Lin
  10. Jimmy Ba

Papers from Bin Fu's perspective

Ordered by how strongly the researchers Bin Fu 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. Attention is All you Need (Neural Information Processing Systems)
  4. ImageNet: A large-scale hierarchical image database
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Long Short-Term Memory
  7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  8. Gradient-based learning applied to document recognition
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers