Jun-Wei Hsieh

Computer Vision and Pattern Recognition · 2006–2019

A researcher in the Science corpus: 3 papers; trusts 133 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

Whom Jun-Wei Hsieh trusts overall

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

  1. Ingrid Daubechies
  2. Scott Weiss
  3. Kaiming He
  4. V. Kastrinaki
  5. Ross B. Girshick
  6. Alex Krizhevsky
  7. Geoffrey E. Hinton
  8. Jia Deng

Who trusts Jun-Wei Hsieh overall

  1. Pallavi Sethi
  2. Norbert Erich Buch
  3. Zhen Dong
  4. Smruti Ranjan Sarangi
  5. Amir Mukhtar
  6. Sergio A. Velastin
  7. Giuseppe Amato
  8. Chien-Yao Wang
  9. Yuwei Wu

Papers from Jun-Wei Hsieh's perspective

Ordered by how strongly the researchers Jun-Wei Hsieh 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: A large-scale hierarchical image database
  3. ImageNet classification with deep convolutional neural networks
  4. Microsoft COCO: Common Objects in Context
  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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Going deeper with convolutions
  10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers