Rana Hanocka

Computer Vision and Pattern Recognition · with Bar-On · 2021–2023

A researcher in the Science corpus: 2 papers; trusts 92 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Rana Hanocka trusts overall

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

  1. Geoffrey E. Hinton
  2. Diederik P. Kingma
  3. Tero Karras
  4. Alex Krizhevsky
  5. Kaiming He
  6. Yoshua Bengio
  7. Alec Radford

Papers from Rana Hanocka's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. ImageNet: A large-scale hierarchical image database
  3. ImageNet classification with deep convolutional neural networks
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. Long Short-Term Memory
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Learning Multiple Layers of Features from Tiny Images

Their papers