Ming Lu

Computer Vision and Pattern Recognition · 1 papers · 2023

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Ming Lu trusts

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

  1. Trevor Darrell (in Computer Vision and Pattern Recognition)
  2. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  3. Kaiming He (in Computer Vision and Pattern Recognition)
  4. Thomas Brox (in Computer Vision and Pattern Recognition)
  5. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  6. Jonathan Long (in Computer Vision and Pattern Recognition)
  7. Evan Shelhamer (in Computer Vision and Pattern Recognition)
  8. Karen Simonyan (in Computer Vision and Pattern Recognition)
  9. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  10. Shaoqing Ren (in Computer Vision and Pattern Recognition)

Papers from Ming Lu's perspective

Ordered by how strongly the researchers Ming Lu trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Attention is All you Need (Neural Information Processing Systems)
  2. Fully convolutional networks for semantic segmentation
  3. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. ImageNet classification with deep convolutional neural networks
  6. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (International Conference on Learning Representations)
  7. ImageNet: A large-scale hierarchical image database
  8. Gradient-based learning applied to document recognition
  9. Going deeper with convolutions
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers