Junehwa Song

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Junehwa Song trusts

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

  1. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  2. Yangqing Jia (in Computer Vision and Pattern Recognition)
  3. Karen Simonyan (in Computer Vision and Pattern Recognition)
  4. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  5. Kaiming He (in Computer Vision and Pattern Recognition)
  6. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  7. Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)
  8. Shaoqing Ren (in Computer Vision and Pattern Recognition)
  9. Ilya Sutskever (in Computer Vision and Pattern Recognition)
  10. X. Zhang (in Computer Vision and Pattern Recognition)

Papers from Junehwa Song's perspective

Ordered by how strongly the researchers Junehwa Song 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. Going deeper with convolutions
  4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  5. Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks
  6. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
  7. How transferable are features in deep neural networks?
  8. Speeding up Convolutional Neural Networks with Low Rank Expansions
  9. Deep Compression: Compressing Deep Neural Network with Pruning, Trained Quantization and Huffman Coding
  10. You Only Look Once: Unified, Real-Time Object Detection

Their papers