Sunghwan Choi

Computer Vision and Pattern Recognition · 2014

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

Subfields

Whom Sunghwan Choi trusts overall

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

  1. Michael Elad
  2. Qingxiong Yang
  3. Dani Lischinski
  4. Eduardo Simoes Lopes Gastal
  5. Rick Chartrand
  6. Xiaobo An
  7. Anat Levin
  8. Li Xu
  9. Zhou Wang

Who trusts Sunghwan Choi overall

  1. Jonathan T. Barron

Papers from Sunghwan Choi's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Image quality assessment: from error visibility to structural similarity
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Bilateral filtering for gray and color images
  5. Colorization using optimization
  6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  7. Gradient-based learning applied to document recognition
  8. ImageNet: A large-scale hierarchical image database
  9. Going deeper with convolutions
  10. A Fast Approximation of the Bilateral Filter Using a Signal Processing Approach (International Journal of Computer Vision)

Their papers