Michael Weber

Computer Vision and Pattern Recognition · with Bäuml · 2011–2016

A researcher in the Science corpus: 2 papers; trusts 376 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Michael Weber trusts overall

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

  1. Ross B. Girshick
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Alex Krizhevsky
  5. Karen Simonyan
  6. Jitendra Malik
  7. Yann LeCun
  8. Lubomir D. Bourdev
  9. Yoshua Bengio
  10. Andrew Zisserman

Who trusts Michael Weber overall

  1. Tete Xiao
  2. Mennatullah Siam
  3. Magnus Wrenninge
  4. Sumanth Chennupati
  5. Senthil Kumar Yogamani
  6. Alex Kendall
  7. Ganesh Sistu
  8. Seongdeok Bang
  9. Zhao Chen
  10. Toshiyuki Motoyoshi

Papers from Michael Weber's perspective

Ordered by how strongly the researchers Michael Weber 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. Gradient-based learning applied to document recognition
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  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