Dihong Gong

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 150 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Dihong Gong trusts overall

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

  1. Ross B. Girshick
  2. Andrew McCallum
  3. Ellen Riloff
  4. Jia Deng
  5. Andrew Carlson
  6. Geoffrey E. Hinton
  7. Nilesh N. Dalvi
  8. Kaiming He
  9. Alex Krizhevsky
  10. Konstantin Shvachko

Papers from Dihong Gong's perspective

Ordered by how strongly the researchers Dihong Gong 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: A large-scale hierarchical image database
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. Going deeper with convolutions
  8. Long Short-Term Memory
  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