David Ferstl

Computer Vision and Pattern Recognition · 2013

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom David Ferstl trusts overall

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

  1. Daniel Scharstein
  2. Antonin Chambolle
  3. Thomas Pock
  4. Zhengyou Zhang
  5. Kaiming He
  6. Heiko Hirschmüller
  7. James Diebel
  8. Ernie Esser
  9. Sebastian Thrun
  10. Johannes Peter Kopf

Who trusts David Ferstl overall

  1. Yinda Zhang
  2. Jonathan T. Barron
  3. Tak-Wai Hui
  4. Yijun Li
  5. Jingyu Yang
  6. Jonas Uhrig
  7. Jiaxiong Qiu
  8. Xinjing Cheng
  9. Thomas A. Funkhouser
  10. Ben Poole

Papers from David Ferstl's perspective

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

Their papers