Peter H. Jin

Computer Vision and Pattern Recognition · 2016–2018

A researcher in the Science corpus: 6 papers; trusts 321 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

Whom Peter H. Jin trusts overall

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

  1. Kaiming He
  2. Yurii E. Nesterov
  3. Alex Krizhevsky
  4. Geoffrey E. Hinton
  5. Karen Simonyan
  6. Ross B. Girshick
  7. Ilya Sutskever
  8. X. Zhang
  9. Christian Szegedy
  10. Sergey Ioffe

Who trusts Peter H. Jin overall

  1. A. Gholami
  2. Jianyu Wang
  3. Hanlin Tang
  4. Bichen Wu
  5. Yuanming Shi
  6. Jihong Park
  7. J. Daily
  8. Zhi Zhou
  9. Ariful Azad
  10. Kurt Keutzer

Papers from Peter H. Jin's perspective

Ordered by how strongly the researchers Peter H. Jin 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. Gradient-based learning applied to document recognition
  5. ImageNet: A large-scale hierarchical image database
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Going deeper with convolutions
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers