Joseph G. Ellis

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Joseph G. Ellis trusts

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

  1. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  2. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  3. Karen Simonyan (in Computer Vision and Pattern Recognition)

Papers from Joseph G. Ellis's perspective

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

  1. ImageNet: A large-scale hierarchical image database
  2. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  3. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
  4. ImageNet classification with deep convolutional neural networks
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
  7. Gradient-based learning applied to document recognition
  8. Long Short-Term Memory
  9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers