Chengyong Wu

Computer Vision and Pattern Recognition · 2014

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

Subfields

Whom Chengyong Wu trusts

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

  1. Yann LeCun (in Computer Vision and Pattern Recognition)

Who trusts Chengyong Wu

  1. Joel S. Emer (in Computer Vision and Pattern Recognition)

Papers from Chengyong Wu's perspective

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

  1. Gradient-based learning applied to document recognition
  2. Improving neural networks by preventing co-adaptation of feature detectors
  3. Building high-level features using large scale unsupervised learning
  4. GradientBased Learning Applied to Document Recognition
  5. Support-Vector Networks
  6. Improving the speed of neural networks on CPUs
  7. An empirical evaluation of deep architectures on problems with many factors of variation
  8. Robust Object Recognition with Cortex-Like Mechanisms
  9. Convolutional neural networks applied to house numbers digit classification
  10. Improving deep neural networks for LVCSR using rectified linear units and dropout

Their papers