Ümit Budak

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 Ümit Budak trusts

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

  1. Lulu Wang (in Biomedical Engineering)
  2. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  3. Karen Simonyan (in Computer Vision and Pattern Recognition)

Papers from Ümit Budak's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  3. High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks
  4. Deep learning for magnification independent breast cancer histopathology image classification (International Conference on Pattern Recognition)
  5. Early Diagnosis of Breast Cancer (Italian National Conference on Sensors)
  6. Breast cancer histopathological image classification using convolutional neural networks with small SE-ResNet module (PLoS ONE)
  7. [Breast cancer]. (Nihon rinsho. Japanese journal of clinical medicine)
  8. Learning Multiple Layers of Features from Tiny Images
  9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  10. Gradient-based learning applied to document recognition

Their papers