Paul Bentley

Computer Vision and Pattern Recognition · 2016–2019

A researcher in the Science corpus: 5 papers; trusts 246 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 94 citations into it
• Artificial Intelligence — 51 citations into it
• Model Architectures — 26 citations into it
• Representation & Self-Supervised Learning — 15 citations into it
• Biomedical Engineering — 10 citations into it
• Optimization & Training — 10 citations into it
• Biophysics — 8 citations into it
• Media Technology — 7 citations into it

Whom Paul Bentley trusts overall

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

1. Christian Szegedy
2. Alex Krizhevsky
3. Yoshua Bengio
4. Sergey Ioffe
5. Geoffrey E. Hinton
6. Kaiming He
7. Diederik P. Kingma
8. Liang-Chieh Chen
9. Ilya Sutskever
10. Ross B. Girshick

Who trusts Paul Bentley overall

1. Liang Chen
2. Tom Eelbode
3. Jeroen Bertels
4. Krishna Chaitanya
5. Eun-Jae Lee
6. Greg Zaharchuk

Papers from Paul Bentley's perspective

Ordered by how strongly the researchers Paul Bentley 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Going deeper with convolutions
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Self-supervised learning for medical image analysis using image context restoration (2019) — 580 citations
• GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks (2018) — 497 citations
• Fully automatic acute ischemic lesion segmentation in DWI using convolutional neural networks (2017) — 278 citations
• DRINet for Medical Image Segmentation (2018) — 301 citations
• ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI (2016) — 525 citations