Yohan Jun

Computer Vision and Pattern Recognition · 2018–2021

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Yohan Jun trusts overall

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

  1. Jiwon Kim
  2. Chao Dong
  3. Viren Jain
  4. Saiprasad Ravishankar
  5. Zhou Wang
  6. Michael Lustig
  7. Kaiming He
  8. Jung Kwon Lee
  9. Junyuan Xie
  10. Ricardo Otazo

Papers from Yohan Jun's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Gradient-based learning applied to document recognition
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. ImageNet: A large-scale hierarchical image database
  5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  7. ImageNet Large Scale Visual Recognition Challenge
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Rethinking the Inception Architecture for Computer Vision
  10. Long Short-Term Memory

Their papers