Nathan Ong

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 31 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Nathan Ong trusts

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

  1. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  2. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  3. Karen Simonyan (in Computer Vision and Pattern Recognition)
  4. Kaiming He (in Computer Vision and Pattern Recognition)
  5. Shaoqing Ren (in Computer Vision and Pattern Recognition)
  6. Li Fei-Fei (in Computer Vision and Pattern Recognition)
  7. X. Zhang (in Computer Vision and Pattern Recognition)
  8. Trevor Darrell (in Computer Vision and Pattern Recognition)
  9. Rob Fergus (in Computer Vision and Pattern Recognition)
  10. Jitendra Malik (in Computer Vision and Pattern Recognition)

Papers from Nathan Ong's perspective

Ordered by how strongly the researchers Nathan Ong 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. Going deeper with convolutions
  3. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  4. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
  5. ImageNet classification with deep convolutional neural networks
  6. Show and tell: A neural image caption generator
  7. Fast R-CNN
  8. Long-term recurrent convolutional networks for visual recognition and description
  9. Large-Scale Video Classification with Convolutional Neural Networks
  10. Describing objects by their attributes

Their papers