John R. Laird

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom John R. Laird trusts overall

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

  1. Geoffrey E. Hinton

Papers from John R. Laird's perspective

Ordered by how strongly the researchers John R. Laird 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. Going deeper with convolutions
  3. This PDF file includes: Materials and Methods
  4. A Fast Learning Algorithm for Deep Belief Nets
  5. Rethinking the Inception Architecture for Computer Vision
  6. Fully convolutional networks for semantic segmentation
  7. ImageNet classification with deep convolutional neural networks
  8. Deep Learning
  9. Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
  10. Gradient-based learning applied to document recognition

Their papers