Thad Starner

Computer Vision and Pattern Recognition · 2000–2017

A researcher in the Science corpus: 8 papers; trusts 44 researchers and is trusted by 55 researchers here, as inferred from the citation graph.

Subfields

Whom Thad Starner trusts overall

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

  1. Lawrence R. Rabiner
  2. Biing-Hwang Fred Juang
  3. Yann LeCun
  4. Sharon L. Oviatt
  5. Geoffrey E. Hinton
  6. Alex Krizhevsky
  7. Sergey Ioffe
  8. Ilya Sutskever
  9. Philip R. Cohen
  10. Christian Szegedy

Who trusts Thad Starner overall

  1. Martha E. Pollack
  2. Oliver J. Woodman
  3. Shashank Priya
  4. David P. Arnold
  5. Mohammed F. Daqaq
  6. Lin Liao
  7. Robert K. Harle
  8. Yu Zheng
  9. Junrui Liang
  10. Luca Rossi

Papers from Thad Starner's perspective

Ordered by how strongly the researchers Thad Starner 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  4. Gradient-based learning applied to document recognition
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Long Short-Term Memory
  8. ImageNet: A large-scale hierarchical image database
  9. Distilling the Knowledge in a Neural Network (arXiv.org)
  10. Learning Multiple Layers of Features from Tiny Images

Their papers