S. Le Guyader

Computer Vision and Pattern Recognition · 2017

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

• Computer Vision and Pattern Recognition — 7 citations into it
• Artificial Intelligence — 6 citations into it

Whom S. Le Guyader trusts overall

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

1. Kaiming He

Papers from S. Le Guyader's perspective

Ordered by how strongly the researchers S. Le Guyader 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. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
3. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
4. ImageNet classification with deep convolutional neural networks
5. The Importance of Skip Connections in Biomedical Image Segmentation
6. Gradient-based learning applied to document recognition
7. Learning Multiple Layers of Features from Tiny Images
8. Going deeper with convolutions
9. Attention is All you Need (Neural Information Processing Systems)
10. Long Short-Term Memory

Their papers

• Automated Training of Deep Convolutional Neural Networks for Cell Segmentation (2017) — 130 citations