Alejandro F Frangi

Computer Vision and Pattern Recognition · 2001–2023

A researcher in the Science corpus: 15 papers; trusts 62 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 82 citations into it; #6,927 of 21,575 by trust here, #6,326 by citations
• Artificial Intelligence — 80 citations into it; #22,415 of 35,345 by trust here, #20,377 by citations
• Radiology, Nuclear Medicine and Imaging — 50 citations into it; #678 of 3,265 by trust here, #735 by citations
• Computational Mechanics — 10 citations into it; #5,986 of 10,001 by trust here, #4,450 by citations
• Media Technology — 8 citations into it
• Computer Graphics and Computer-Aided Design — 7 citations into it
• Model Architectures — 7 citations into it
• Geometry and Topology — 6 citations into it; #6,154 of 7,422 by trust here, #4,201 by citations

Whom Alejandro F Frangi trusts overall

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

1. Alex Krizhevsky
2. Diederik P. Kingma
3. Kaiming He
4. Geoffrey E. Hinton
5. Karen Simonyan
6. John J. Hopfield
7. Yoshua Bengio
8. Paul J. Werbos
9. Ilya Sutskever
10. Yann LeCun

Who trusts Alejandro F Frangi overall

1. Arvid Lundervold
2. Alexander Andreopoulos
3. Tobias Heimann
4. William R. Crum
5. Juan Eugenio Iglesias
6. Xin Yi
7. Daniel Rueckert
8. M. Avendi
9. Xiahai Zhuang
10. John K. Tsotsos

Papers from Alejandro F Frangi's perspective

Ordered by how strongly the researchers Alejandro F Frangi 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
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. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Active shape model segmentation with optimal features (2002) — 606 citations
• Automatic construction of 3-D statistical deformation models of the brain using nonrigid registration (2003) — 489 citations
• Why rankings of biomedical image analysis competitions should be interpreted with care (2018) — 393 citations
• FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare (2023) — 491 citations
• Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 (2018) — 185 citations
• Simulation and Synthesis in Medical Imaging (2018) — 168 citations
• Semi-supervised Assessment of Incomplete LV Coverage in Cardiac MRI Using Generative Adversarial Nets (2017) — 50 citations
• Statistical shape modeling of the left ventricle: myocardial infarct classification challenge (2017) — 91 citations
• Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015 (2015) — 372 citations
• Statistical Shape Modeling Using Partial Least Squares: Application to the Assessment of Myocardial Infarction (2015) — 13 citations
• KPCA plus LDA: a complete kernel Fisher discriminant framework for feature extraction and recognition (2005) — 899 citations
• Efficient pipeline for image-based patient-specific analysis of cerebral aneurysm hemodynamics: technique and sensitivity (2005) — 614 citations
• Two-dimensional PCA: a new approach to appearance-based face representation and recognition (2004) — 3,748 citations
• Automatic construction of multiple-object three-dimensional statistical shape models: application to cardiac modeling (2002) — 431 citations
• Three-dimensional modeling for functional analysis of cardiac images, a review (2001) — 632 citations