Hak Gu Kim

Computer Vision and Pattern Recognition · 2018

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 Hak Gu Kim trusts overall

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

  1. Karen Simonyan

Papers from Hak Gu Kim's perspective

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

  1. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  2. GENERATIVE ADVERSARIAL NETS
  3. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  4. Rectifier Nonlinearities Improve Neural Network Acoustic Models
  5. ImageNet classification with deep convolutional neural networks
  6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  7. Gradient-based learning applied to document recognition
  8. THE DIGITAL DATABASE FOR SCREENING MAMMOGRAPHY
  9. Learning Multiple Layers of Features from Tiny Images
  10. Receiver operating characteristic analysis: a tool for the quantitative evaluation of observer performance and imaging systems. (Journal of the American College of Radiology)

Their papers