Miriam Hägele

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Miriam Hägele trusts overall

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

  1. Karen Simonyan

Who trusts Miriam Hägele overall

  1. Wojciech Samek

Papers from Miriam Hägele's perspective

Ordered by how strongly the researchers Miriam Hägele 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. ImageNet: A large-scale hierarchical image database
  4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  5. Visualizing and Understanding Convolutional Networks
  6. Rethinking the Inception Architecture for Computer Vision
  7. Gradient-based learning applied to document recognition
  8. Densely Connected Convolutional Networks
  9. Learning Multiple Layers of Features from Tiny Images
  10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers