Bryan Seybold

Computer Vision and Pattern Recognition · 2016–2025

A researcher in the Science corpus: 5 papers; trusts 483 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Bryan Seybold trusts overall

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

  1. Ross B. Girshick
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Alex Krizhevsky
  5. Karen Simonyan
  6. Andrew Zisserman
  7. Diederik P. Kingma
  8. Yann LeCun
  9. Yoshua Bengio
  10. Jitendra Malik

Who trusts Bryan Seybold overall

  1. Wenguan Wang

Papers from Bryan Seybold's perspective

Ordered by how strongly the researchers Bryan Seybold 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. ImageNet: A large-scale hierarchical image database
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. Long Short-Term Memory
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Going deeper with convolutions
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers