Marco Seeland

Computer Vision and Pattern Recognition · 2011–2018

A researcher in the Science corpus: 3 papers; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Marco Seeland trusts overall

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

  1. Sue Han Lee
  2. Kaiming He
  3. Marcel Simon
  4. Jana Wäldchen

Papers from Marco Seeland's perspective

Ordered by how strongly the researchers Marco Seeland 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. ImageNet: A large-scale hierarchical image database
  3. ImageNet classification with deep convolutional neural networks
  4. Going deeper with convolutions
  5. Gradient-based learning applied to document recognition
  6. Automated Flower Classification over a Large Number of Classes
  7. ImageNet Large Scale Visual Recognition Challenge
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  10. Long Short-Term Memory

Their papers