Yuanhan Mo
Artificial Intelligence · 2017
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
- Artificial Intelligence — 5 citations into it
Whom Yuanhan Mo trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma (in Artificial Intelligence)
- Jimmy Ba (in Artificial Intelligence)
Papers from Yuanhan Mo's perspective
Ordered by how strongly the researchers Yuanhan Mo trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Fully convolutional networks for semantic segmentation
- U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
- Best practices for convolutional neural networks applied to visual document analysis
- Brain tumor segmentation with Deep Neural Networks
- V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
- ImageNet classification with deep convolutional neural networks
- Efficient multi‐scale 3D CNN with fully connected CRF for accurate brain lesion segmentation
- Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017: 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part II
- Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images (IEEE Transactions on Medical Imaging)