Dirk Ebersbach

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Dirk Ebersbach trusts

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

  1. Shaoqing Ren (in Computer Vision and Pattern Recognition)
  2. Kaiming He (in Computer Vision and Pattern Recognition)
  3. Christian Szegedy (in Artificial Intelligence)
  4. X. Zhang (in Computer Vision and Pattern Recognition)
  5. Sergey Ioffe (in Artificial Intelligence)
  6. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  7. Karen Simonyan (in Computer Vision and Pattern Recognition)
  8. Alex Krizhevsky (in Computer Vision and Pattern Recognition)

Papers from Dirk Ebersbach's perspective

Ordered by how strongly the researchers Dirk Ebersbach 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  5. Dropout: a simple way to prevent neural networks from overfitting
  6. Rethinking the Inception Architecture for Computer Vision
  7. Caffe: Convolutional Architecture for Fast Feature Embedding
  8. Identity Mappings in Deep Residual Networks
  9. Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
  10. Gradient-based learning applied to document recognition

Their papers