Boah Kim

Radiology, Nuclear Medicine and Imaging · 2020

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 Boah Kim trusts overall

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

  1. Bruce Fischl
  2. Guha Balakrishnan
  3. Brian B. Avants
  4. Olaf Ronneberger
  5. Xiao Yang
  6. Max Jaderberg
  7. Mirza Faisal Beg
  8. Stefan Klein
  9. Hessam Sokooti
  10. Amy Zhao

Papers from Boah Kim's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. Spatial Transformer Networks
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  6. Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms (International Journal of Computer Vision)
  7. Gradient-based learning applied to document recognition
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. A fast diffeomorphic image registration algorithm (NeuroImage)
  10. Learning Multiple Layers of Features from Tiny Images

Their papers