Steve B. Jiang

Computer Vision and Pattern Recognition · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Steve B. Jiang trusts

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

  1. Yann LeCun (in Computer Vision and Pattern Recognition)
  2. Trevor Darrell (in Computer Vision and Pattern Recognition)
  3. Yoshua Bengio (in Computer Vision and Pattern Recognition)
  4. L. Eon Bottou (in Computer Vision and Pattern Recognition)
  5. Jonathan Long (in Computer Vision and Pattern Recognition)
  6. Evan Shelhamer (in Computer Vision and Pattern Recognition)
  7. Patrick Haffner (in Computer Vision and Pattern Recognition)

Papers from Steve B. Jiang's perspective

Ordered by how strongly the researchers Steve B. Jiang 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. Gradient-based learning applied to document recognition
  4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  5. Rectified Linear Units Improve Restricted Boltzmann Machines
  6. Fully convolutional networks for semantic segmentation
  7. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  8. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
  9. Learning Deconvolution Network for Semantic Segmentation
  10. Object Recognition with Gradient-Based Learning

Their papers