S. Speidel

Computer Vision and Pattern Recognition · 2013–2020

A researcher in the Science corpus: 6 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom S. Speidel trusts

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

  1. Andrew Zisserman (in Computer Vision and Pattern Recognition)

Papers from S. Speidel's perspective

Ordered by how strongly the researchers S. Speidel 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  6. Fully convolutional networks for semantic segmentation
  7. Caffe: Convolutional Architecture for Fast Feature Embedding
  8. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  9. Unbiased look at dataset bias
  10. Are we ready for autonomous driving? The KITTI vision benchmark suite

Their papers