Thomas Ganslandt

Computer Vision and Pattern Recognition · 2022

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Thomas Ganslandt trusts

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

  1. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  2. Shaoqing Ren (in Computer Vision and Pattern Recognition)
  3. Kaiming He (in Computer Vision and Pattern Recognition)
  4. Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)
  5. Ilya Sutskever (in Computer Vision and Pattern Recognition)

Papers from Thomas Ganslandt's perspective

Ordered by how strongly the researchers Thomas Ganslandt 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. Going deeper with convolutions
  5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  6. Histograms of oriented gradients for human detection
  7. GENERATIVE ADVERSARIAL NETS
  8. Network In Network
  9. A Survey on Transfer Learning
  10. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (International Conference on Learning Representations)

Their papers