Song-Le Chen

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Song-Le Chen trusts

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

  1. Vladimir Kolmogorov (in Computer Vision and Pattern Recognition)
  2. Leonidas J. Guibas (in Computer Vision and Pattern Recognition)

Papers from Song-Le Chen's perspective

Ordered by how strongly the researchers Song-Le Chen trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Volumetric and Multi-view CNNs for Object Classification on 3D Data
  2. Holistically-Nested Edge Detection
  3. Gradient-based learning applied to document recognition
  4. ImageNet classification with deep convolutional neural networks
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Joint shape segmentation with linear programming
  7. What energy functions can be minimized via graph cuts?
  8. Recurrent Convolutional Neural Networks for Scene Labeling
  9. Learning Convolutional Neural Networks for Graphs
  10. 3D Shape Segmentation with Projective Convolutional Networks

Their papers