Peter M. Full

Computer Vision and Pattern Recognition · 2018–2021

A researcher in the Science corpus: 4 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Peter M. Full trusts overall

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

  1. Kaiming He

Papers from Peter M. Full's perspective

Ordered by how strongly the researchers Peter M. Full 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: A large-scale hierarchical image database
  3. Fully convolutional networks for semantic segmentation
  4. ImageNet classification with deep convolutional neural networks
  5. Densely Connected Convolutional Networks
  6. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  7. Gradient-based learning applied to document recognition
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers