Paul Scheunders

Media Technology · 2013–2018

A researcher in the Science corpus: 4 papers; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Paul Scheunders trusts overall

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

  1. José M. Bioucas-Dias
  2. Shen-En Qian
  3. Jose M. P. Nascimento
  4. Farid Melgani
  5. David L. Donoho
  6. Qiangqiang Yuan
  7. Lorenzo Bruzzone
  8. Liangpei Zhang
  9. Wei He
  10. Hisham Othman

Papers from Paul Scheunders's perspective

Ordered by how strongly the researchers Paul Scheunders 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Gradient-based learning applied to document recognition
  6. ImageNet: A large-scale hierarchical image database
  7. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
  8. Going deeper with convolutions
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Long Short-Term Memory

Their papers