Nathan S. Lay

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 39 citations into it

Whom Nathan S. Lay trusts overall

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

1. Brian B. Avants
2. Saining Xie

Who trusts Nathan S. Lay overall

1. Arvid Lundervold

Papers from Nathan S. Lay's perspective

Ordered by how strongly the researchers Nathan S. Lay 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. Fully convolutional networks for semantic segmentation
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet Large Scale Visual Recognition Challenge
7. ImageNet: A large-scale hierarchical image database
8. Going deeper with convolutions
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Long Short-Term Memory

Their papers

• Spatial aggregation of holistically‐nested convolutional neural networks for automated pancreas localization and segmentation☆ (2017) — 300 citations
• Automatic magnetic resonance prostate segmentation by deep learning with holistically nested networks (2017) — 66 citations