Fausto Milletarì

Computer Vision and Pattern Recognition · 2015–2020

A researcher in the Science corpus: 8 papers; trusts 215 researchers and is trusted by 180 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 87 citations into it; #2,712 of 21,575 by trust here, #2,091 by citations
• Artificial Intelligence — 81 citations into it
• Model Architectures — 24 citations into it
• Optimization & Training — 16 citations into it
• Biophysics — 8 citations into it
• Medical Imaging — 7 citations into it
• Evaluation & Benchmarks — 6 citations into it
• Media Technology — 6 citations into it

Whom Fausto Milletarì trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Evan Shelhamer
5. X. Zhang
6. Ross B. Girshick
7. Yann LeCun
8. Yoshua Bengio
9. Shaoqing Ren
10. Diederik P. Kingma

Who trusts Fausto Milletarì overall

1. Guotai Wang
2. Qi-Yan Dou
3. Bowen Cheng
4. Fabian Isensee
5. Lequan Yu
6. Wenhai Wang
7. Dong Yang
8. Golnaz Ghiasi
9. Arvid Lundervold
10. Andriy Myronenko

Papers from Fausto Milletarì's perspective

Ordered by how strongly the researchers Fausto Milletarì 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. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation (2016) — 11,050 citations
• Hough-CNN: Deep learning for segmentation of deep brain regions in MRI and ultrasound (2016) — 378 citations
• The future of digital health with federated learning (2020) — 2,960 citations
• Privacy-preserving Federated Brain Tumour Segmentation (2019) — 562 citations
• Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation (2019) — 50 citations
• CFCM: Segmentation via Coarse to Fine Context Memory (2018) — 50 citations
• Standardized Evaluation System for Left Ventricular Segmentation Algorithms in 3D Echocardiography (2016) — 104 citations
• Multimodal image-guided prostate fusion biopsy based on automatic deformable registration (2015) — 75 citations