Qi Guo

Computer Vision and Pattern Recognition · with Chen · 2016

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Qi Guo trusts

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

  1. Yann LeCun (in Computer Vision and Pattern Recognition)
  2. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  3. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  4. Karen Simonyan (in Computer Vision and Pattern Recognition)

Papers from Qi Guo's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Gradient-based learning applied to document recognition
  3. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  4. Dropout: a simple way to prevent neural networks from overfitting
  5. Building high-level features using large scale unsupervised learning
  6. Caffe: Convolutional Architecture for Fast Feature Embedding
  7. What is the best multi-stage architecture for object recognition?
  8. Emergence of simple-cell receptive field properties by learning a sparse code for natural images
  9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  10. Sparse deep belief net model for visual area V2

Their papers