Giacomo Tarroni

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 4 papers; trusts 59 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 76 citations into it
• Artificial Intelligence — 57 citations into it
• Radiology, Nuclear Medicine and Imaging — 43 citations into it
• Model Architectures — 21 citations into it
• Biomedical Engineering — 20 citations into it

Whom Giacomo Tarroni trusts overall

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

1. Diederik P. Kingma
2. Kaiming He
3. Geoffrey E. Hinton
4. Karen Simonyan
5. Alex Krizhevsky
6. Christian Szegedy
7. Yoshua Bengio
8. Yann LeCun
9. Evan Shelhamer
10. Sergey Ioffe

Papers from Giacomo Tarroni's perspective

Ordered by how strongly the researchers Giacomo Tarroni 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 classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Going deeper with convolutions
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Semi-supervised Learning for Network-Based Cardiac MR Image Segmentation (2017) — 431 citations
• Deep Learning for Cardiac Image Segmentation: A Review (2019) — 844 citations
• Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling (2018) — 77 citations
• Automated cardiovascular magnetic resonance image analysis with fully convolutional networks (2017) — 706 citations