Jin Tae Kwak

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 4 papers; trusts 35 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jin Tae Kwak trusts overall

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

  1. Kaiming He

Papers from Jin Tae Kwak's perspective

Ordered by how strongly the researchers Jin Tae Kwak 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. ImageNet Large Scale Visual Recognition Challenge
  5. ImageNet: A large-scale hierarchical image database
  6. Going deeper with convolutions
  7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  8. Microsoft COCO: Common Objects in Context
  9. Fully convolutional networks for semantic segmentation
  10. Rethinking the Inception Architecture for Computer Vision

Their papers