Yu-Shiang Wong

Computer Vision and Pattern Recognition · with Li · 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 Yu-Shiang Wong trusts overall

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

  1. Martin Rünz
  2. Brian Curless
  3. Kaiming He
  4. Lourdes de Agapito
  5. Michael Strecke
  6. Emanuele Palazzolo
  7. Marc Levoy
  8. Ross B. Girshick
  9. Rainer Stiefelhagen
  10. Jörg Stückler

Papers from Yu-Shiang Wong's perspective

Ordered by how strongly the researchers Yu-Shiang Wong 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. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet Large Scale Visual Recognition Challenge
  8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. Going deeper with convolutions
  10. Long Short-Term Memory

Their papers