Mu-Han Lin

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 12 citations into it

Whom Mu-Han Lin trusts overall

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

1. Yann LeCun

Papers from Mu-Han Lin's perspective

Ordered by how strongly the researchers Mu-Han Lin trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Gradient-based learning applied to document recognition
3. Rectified Linear Units Improve Restricted Boltzmann Machines
4. Backpropagation Applied to Handwritten Zip Code Recognition
5. Fully convolutional networks for semantic segmentation
6. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
7. ImageNet classification with deep convolutional neural networks
8. Learning Deconvolution Network for Semantic Segmentation
9. Learning Multiple Layers of Features from Tiny Images
10. Long Short-Term Memory

Their papers

• 3D radiotherapy dose prediction on head and neck cancer patients with a hierarchically densely connected U-net deep learning architecture (2018) — 324 citations