Berkin Bilgic

Radiology, Nuclear Medicine and Imaging · 2011–2018

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Berkin Bilgic trusts overall

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

  1. Torsten Rohlfing
  2. Mark Jenkinson
  3. Stephen M. Smith
  4. ProblemsPer Christian HansenDepartment
  5. Tian Liu
  6. Ferdinand Schweser
  7. Jeff H. Duyn
  8. Calvin R. Maurer Jr.
  9. Xavier Glorot
  10. Yi Wang

Papers from Berkin Bilgic's perspective

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

  1. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  2. ImageNet classification with deep convolutional neural networks
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Understanding the difficulty of training deep feedforward neural networks
  6. Gradient-based learning applied to document recognition
  7. Caffe: Convolutional Architecture for Fast Feature Embedding
  8. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  9. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers