Andrew L Beers

Artificial Intelligence · 2017–2018

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

Subfields

• Artificial Intelligence — 13 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it
• Optimization & Training — 8 citations into it

Whom Andrew L Beers trusts

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

1. Hang Su (in Artificial Intelligence)

Papers from Andrew L Beers's perspective

Ordered by how strongly the researchers Andrew L Beers 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. ImageNet Large Scale Visual Recognition Challenge
3. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
4. Dropout: a simple way to prevent neural networks from overfitting
5. Large Scale Distributed Deep Networks
6. A Survey on Transfer Learning
7. Deep Learning
8. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.
9. Dermatologist-level classification of skin cancer with deep neural networks
10. Multi-task transfer learning deep convolutional neural network: Application to computer-aided diagnosis of breast cancer on mammograms

Their papers

• Distributed deep learning networks among institutions for medical imaging (2018) — 315 citations
• Residual Convolutional Neural Network for Determination of IDH Status in Low- and High-grade Gliomas from MR Imaging (2017) — 336 citations