Frank T. Mücklich

Computer Vision and Pattern Recognition · 2000–2019

A researcher in the Science corpus: 7 papers; trusts 16 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

Whom Frank T. Mücklich trusts overall

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

  1. Andrew Zisserman
  2. Karen Simonyan
  3. Bill Triggs
  4. Navneet Dalal
  5. Yann LeCun
  6. J. Urgen Schmidhuber
  7. Trevor Darrell
  8. Yoshua Bengio
  9. Alex Krizhevsky
  10. Jia Deng

Who trusts Frank T. Mücklich overall

  1. Jörg Schröder
  2. Volker Schmidt
  3. D. Trias
  4. Aul
  5. Evgueni Spodarev

Papers from Frank T. Mücklich's perspective

Ordered by how strongly the researchers Frank T. Mücklich trusts endorse each paper. Same corpus, a different order for every researcher.

  1. ImageNet classification with deep convolutional neural networks
  2. Gradient-based learning applied to document recognition
  3. ImageNet: A large-scale hierarchical image database
  4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  5. Histograms of oriented gradients for human detection
  6. DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
  7. Fully convolutional networks for semantic segmentation
  8. Caffe: Convolutional Architecture for Fast Feature Embedding
  9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  10. Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position

Their papers