Jun-Pyo Hong

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 22 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jun-Pyo Hong trusts overall

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

  1. Ross B. Girshick

Papers from Jun-Pyo Hong's perspective

Ordered by how strongly the researchers Jun-Pyo Hong 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. ImageNet classification with deep convolutional neural networks
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. ImageNet: A large-scale hierarchical image database
  5. Gradient-based learning applied to document recognition
  6. ImageNet Large Scale Visual Recognition Challenge
  7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Going deeper with convolutions
  10. Long Short-Term Memory

Their papers