Arnau Oliver

Computer Vision and Pattern Recognition · 2010–2017

A researcher in the Science corpus: 4 papers; trusts 148 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 138 citations into it
• Artificial Intelligence — 72 citations into it
• Radiology, Nuclear Medicine and Imaging — 37 citations into it
• Model Architectures — 33 citations into it
• Optimization & Training — 26 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Arnau Oliver trusts overall

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

1. Radford M. Neal
2. Kenneth M. Rose
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Yann LeCun
6. Paul A. Viola
7. Alex Krizhevsky
8. Kaiming He
9. Arthur P. Dempster
10. Julian Besag

Who trusts Arnau Oliver overall

1. Maciej A. Mazurowski
2. Rahimeh Rouhi
3. Alireza Norouzi

Papers from Arnau Oliver's perspective

Ordered by how strongly the researchers Arnau Oliver 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Going deeper with convolutions
8. ImageNet Large Scale Visual Recognition Challenge
9. Long Short-Term Memory
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A review of atlas-based segmentation for magnetic resonance brain images (2011) — 471 citations
• A review of automatic mass detection and segmentation in mammographic images (2010) — 435 citations
• Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review (2017) — 385 citations
• Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach (2017) — 391 citations