Tim Brooks

Computer Vision and Pattern Recognition · 2018–2022

A researcher in the Science corpus: 3 papers; trusts 326 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Tim Brooks trusts overall

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

  1. Diederik P. Kingma
  2. Geoffrey E. Hinton
  3. Kaiming He
  4. Alex Krizhevsky
  5. Yoshua Bengio
  6. Jonathan Ho
  7. Yann LeCun
  8. J. Urgen Schmidhuber
  9. Ilya Sutskever
  10. Jimmy Ba

Who trusts Tim Brooks overall

  1. Syed Waqas Zamir
  2. Haotian Liu
  3. Tao Yang
  4. Omer Bar-Tal
  5. Chenshuang Zhang
  6. Jing Shi
  7. Mingqiao Ye
  8. Shuai Yang
  9. Lin Song
  10. Shaoteng Liu

Papers from Tim Brooks's perspective

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

Their papers