Malcolm Slaney

Signal Processing · 2001–2022

A researcher in the Science corpus: 6 papers; trusts 3 researchers and is trusted by 28 researchers here, as inferred from the citation graph.

Subfields

Whom Malcolm Slaney trusts overall

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

  1. Masataka Goto

Who trusts Malcolm Slaney overall

  1. T. Heindel
  2. Jeffrey A. Fessler
  3. Masaharu Sakamoto
  4. Willem Jan Palenstijn
  5. I. Amenabar
  6. Oguz Semerci
  7. Yifei Lou
  8. Beat Münch
  9. A. Fercher
  10. Hugo Leclerc

Papers from Malcolm Slaney's perspective

Ordered by how strongly the researchers Malcolm Slaney 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  6. Dropout: a simple way to prevent neural networks from overfitting
  7. Rectified Linear Units Improve Restricted Boltzmann Machines
  8. Rethinking the Inception Architecture for Computer Vision
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Gradient-based learning applied to document recognition

Their papers