Enzo Ferrante

Computer Vision and Pattern Recognition · 2016–2023

A researcher in the Science corpus: 11 papers; trusts 383 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 147 citations into it
• Artificial Intelligence — 132 citations into it; #34,660 of 35,345 by trust here, #10,667 by citations
• Radiology, Nuclear Medicine and Imaging — 83 citations into it
• Cognitive Neuroscience — 41 citations into it
• Graph Learning — 34 citations into it
• Model Architectures — 26 citations into it
• Representation & Self-Supervised Learning — 22 citations into it
• Computational Mechanics — 21 citations into it

Whom Enzo Ferrante trusts overall

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

1. David G. Lowe
2. Geoffrey E. Hinton
3. Christian Szegedy
4. Yuri Boykov
5. Alex Krizhevsky
6. Yann LeCun
7. Diederik P. Kingma
8. Kaiming He
9. Yoshua Bengio
10. Karen Simonyan

Who trusts Enzo Ferrante overall

1. Sarah Parisot
2. Xiao-Meng Zhang
3. Xingyu Jiang
4. Jiayi Ma
5. Nathanael Perraudin
6. Arvid Lundervold
7. Andriy Myronenko
8. Federico Monti
9. Fabian Isensee

Papers from Enzo Ferrante's perspective

Ordered by how strongly the researchers Enzo Ferrante 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis (2020) — 627 citations
• Distance Metric Learning Using Graph Convolutional Networks: Application to Functional Brain Networks (2017) — 216 citations
• Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation (2017) — 732 citations
• FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare (2023) — 491 citations
• Domain Generalization via Gradient Surgery (2021) — 105 citations
• Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease (2018) — 743 citations
• Metric learning with spectral graph convolutions on brain connectivity networks (2018) — 375 citations
• Spectral Graph Convolutions for Population-based Disease Prediction (2017) — 250 citations
• Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation (2017) — 460 citations
• Slice-to-volume medical image registration: a survey (2017) — 181 citations
• DeepMedic for Brain Tumor Segmentation (2016) — 325 citations