Michael Gleicher

Computer Vision and Pattern Recognition · 2001–2016

A researcher in the Science corpus: 8 papers; trusts 46 researchers and is trusted by 53 researchers here, as inferred from the citation graph.

Subfields

Whom Michael Gleicher trusts overall

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

  1. Geoffrey E. Hinton
  2. Jeffrey Heer
  3. Yoshua Bengio
  4. Matthew Brand
  5. Tamara Munzner
  6. Vittorio Castelli
  7. Brett Allen
  8. Alex Krizhevsky
  9. Dumitru Erhan
  10. Aaron E. Darling

Who trusts Michael Gleicher overall

  1. Leslie Ikemoto
  2. Jinxiang Chai
  3. Jongbin Jung
  4. Johannes Peter Kopf
  5. Matthias Grundmann
  6. Jessica K. Hodgins
  7. Mohamed A. Elgharib
  8. Alla Safonova
  9. Gesina Schwalbe
  10. Meinard Müller

Papers from Michael Gleicher's perspective

Ordered by how strongly the researchers Michael Gleicher 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Gradient-based learning applied to document recognition
  5. Long Short-Term Memory
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet: A large-scale hierarchical image database
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Going deeper with convolutions

Their papers