Nam Huynh

Biomedical Engineering · 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 Nam Huynh trusts

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

  1. Paul C. Beard (in Radiology, Nuclear Medicine and Imaging)
  2. Otmar Scherzer (in Modeling and Simulation)

Papers from Nam Huynh's perspective

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

  1. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  2. Learning to learn by gradient descent by gradient descent
  3. Compressed Sensing
  4. Deep Convolutional Neural Network for Inverse Problems in Imaging (IEEE Transactions on Image Processing)
  5. Solving ill-posed inverse problems using iterative deep neural networks
  6. A deep convolutional neural network using directional wavelets for low‐dose X‐ray CT reconstruction (Medical Physics (Lancaster))
  7. Biomedical photoacoustic imaging (Interface Focus)
  8. Single-pixel imaging via compressive sampling (IEEE Signal Processing Magazine)
  9. Learned Primal-Dual Reconstruction (IEEE Transactions on Medical Imaging)
  10. Mathematics of Deep Learning

Their papers