Michael Baumgartner

Computer Vision and Pattern Recognition · International Conference on Medical Image Computing and Computer-Assisted Intervention · 2022–2024

A researcher in the Science corpus: 4 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Michael Baumgartner trusts overall

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

  1. Kaiming He
  2. Karen Simonyan
  3. Ali Hatamizadeh

Papers from Michael Baumgartner's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. Attention is All you Need (Neural Information Processing Systems)
  3. ImageNet: A large-scale hierarchical image database
  4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  5. ImageNet classification with deep convolutional neural networks
  6. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (International Conference on Learning Representations)
  7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  8. Gradient-based learning applied to document recognition
  9. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers