Buer Chen

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Buer Chen trusts

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

  1. Quoc V. Le (in Computer Vision and Pattern Recognition)
  2. Tsung-Yi Lin (in Computer Vision and Pattern Recognition)
  3. Christian Szegedy (in Artificial Intelligence)

Papers from Buer Chen's perspective

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

  1. Going deeper with convolutions
  2. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  3. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  4. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  5. DropBlock: A regularization method for convolutional networks
  6. NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection
  7. ImageNet classification with deep convolutional neural networks
  8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  9. Gradient-based learning applied to document recognition
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers