Tat-Jun Chin

Computer Vision and Pattern Recognition · 2013–2016

A researcher in the Science corpus: 2 papers; trusts 35 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Tat-Jun Chin trusts overall

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

  1. Andrea Vedaldi
  2. Victor S. Lempitsky
  3. Gaël Guennebaud
  4. Takeo Igarashi
  5. Scott Schaefer
  6. Andriy Myronenko
  7. Junhong Gao
  8. Andrew Zisserman
  9. Feng Liu

Who trusts Tat-Jun Chin overall

  1. Fan Zhang

Papers from Tat-Jun Chin's perspective

Ordered by how strongly the researchers Tat-Jun Chin 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. Gradient-based learning applied to document recognition
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. ImageNet: A large-scale hierarchical image database
  6. ImageNet Large Scale Visual Recognition Challenge
  7. Going deeper with convolutions
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Long Short-Term Memory

Their papers