Joseph Heyward

Computer Vision and Pattern Recognition · 2023–2025

A researcher in the Science corpus: 3 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Joseph Heyward trusts

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

  1. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  2. Kaiming He (in Computer Vision and Pattern Recognition)
  3. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  4. Rob Fergus (in Computer Vision and Pattern Recognition)
  5. Jitendra Malik (in Computer Vision and Pattern Recognition)
  6. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  7. João Carreira (in Computer Vision and Pattern Recognition)
  8. Deva Ramanan (in Computer Vision and Pattern Recognition)
  9. Yann LeCun (in Computer Vision and Pattern Recognition)
  10. Shaoqing Ren (in Computer Vision and Pattern Recognition)

Papers from Joseph Heyward's perspective

Ordered by how strongly the researchers Joseph Heyward trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Gradient-based learning applied to document recognition
  2. ImageNet: A large-scale hierarchical image database
  3. Human-level control through deep reinforcement learning
  4. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (International Conference on Learning Representations)
  5. Unsupervised Learning of Video Representations using LSTMs
  6. ImageNet classification with deep convolutional neural networks
  7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  8. Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Overcoming catastrophic forgetting in neural networks

Their papers