Richard Kuzma

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Richard Kuzma trusts overall

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

  1. Ross B. Girshick
  2. Kaiming He
  3. Shaoqing Ren
  4. Alex Krizhevsky
  5. Geoffrey E. Hinton
  6. Oriol Vinyals
  7. Jifeng Dai
  8. Tsung-Yi Lin
  9. Ilya Sutskever
  10. Yann LeCun

Papers from Richard Kuzma's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. ImageNet Large Scale Visual Recognition Challenge
  4. Gradient-based learning applied to document recognition
  5. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. ImageNet: A large-scale hierarchical image database
  8. Long Short-Term Memory
  9. Microsoft COCO: Common Objects in Context
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers