Nasour Bagheri

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Nasour Bagheri trusts overall

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

  1. Alex Krizhevsky
  2. Ha Hong
  3. Daniel L. K. Yamins
  4. Seyed-Mahdi Khaligh-Razavi
  5. Geoffrey E. Hinton
  6. David G. Lowe
  7. Ilya Sutskever
  8. James J. DiCarlo
  9. Franccois Fleuret

Papers from Nasour Bagheri's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Distinctive Image Features from Scale-Invariant Keypoints
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
  5. Histograms of oriented gradients for human detection
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. ImageNet Large Scale Visual Recognition Challenge
  9. Long Short-Term Memory
  10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers