SeoungHyun Go

Computer Vision and Pattern Recognition · 2021

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 SeoungHyun Go trusts overall

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

  1. Ross B. Girshick
  2. Ilya Loshchilov
  3. Jia Deng

Papers from SeoungHyun Go's perspective

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

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

Their papers