Mia Polansky

Computer Vision and Pattern Recognition · 2016

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Mia Polansky trusts

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

  1. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  2. Andrea Vedaldi (in Computer Vision and Pattern Recognition)
  3. Yann LeCun (in Computer Vision and Pattern Recognition)
  4. Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)
  5. Ilya Sutskever (in Computer Vision and Pattern Recognition)
  6. Aravindh Mahendran (in Computer Vision and Pattern Recognition)

Papers from Mia Polansky's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Going deeper with convolutions
  3. Understanding deep image representations by inverting them
  4. Gradient-based learning applied to document recognition
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Convolutional networks and applications in vision
  7. Attention is All you Need (Neural Information Processing Systems)
  8. DianNao: a small-footprint high-throughput accelerator for ubiquitous machine-learning
  9. NeuFlow: Dataflow vision processing system-on-a-chip
  10. A/D converter trends: Power dissipation, scaling and digitally assisted architectures (IEEE Custom Integrated Circuits Conference)

Their papers