Miriam Leeser

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 Miriam Leeser trusts

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

  1. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  2. Yann LeCun (in Computer Vision and Pattern Recognition)
  3. Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)

Papers from Miriam Leeser's perspective

Ordered by how strongly the researchers Miriam Leeser 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. Learning both Weights and Connections for Efficient Neural Network
  4. Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation
  5. XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
  6. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
  7. In-datacenter performance analysis of a tensor processing unit
  8. YOLO9000: Better, Faster, Stronger
  9. DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients
  10. SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <1MB model size

Their papers