Tom Kamiel Magda Vercauteren

Computer Vision and Pattern Recognition · 2007–2022

A researcher in the Science corpus: 16 papers; trusts 271 researchers and is trusted by 25 researchers here, as inferred from the citation graph.

Subfields

Computer Vision and Pattern Recognition — 237 citations into it; #5,109 of 21,575 by trust here, #1,996 by citations
Artificial Intelligence — 109 citations into it
Radiology, Nuclear Medicine and Imaging — 51 citations into it; #2,913 of 3,265 by trust here, #377 by citations
Model Architectures — 45 citations into it
Biomedical Engineering — 41 citations into it
Biophysics — 21 citations into it
Computational Mechanics — 20 citations into it; #9,240 of 10,001 by trust here, #5,350 by citations
Aerospace Engineering — 18 citations into it; #889 of 6,421 by trust here, #1,402 by citations

Whom Tom Kamiel Magda Vercauteren trusts overall

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

Who trusts Tom Kamiel Magda Vercauteren overall

Papers from Tom Kamiel Magda Vercauteren's perspective

Ordered by how strongly the researchers Tom Kamiel Magda Vercauteren trusts endorse each paper. Same corpus, a different order for every researcher.

ImageNet classification with deep convolutional neural networks
Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Gradient-based learning applied to document recognition
Going deeper with convolutions
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Long Short-Term Memory
ImageNet: A large-scale hierarchical image database
Attention is All you Need (Neural Information Processing Systems)

Their papers

DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation (2017) — 476 citations
Automatic Brain Tumor Segmentation Using Cascaded Anisotropic Convolutional Neural Networks (2017) — 546 citations
Generalised Dice Overlap as a Deep Learning Loss Function for Highly Unbalanced Segmentations (2017) — 2,736 citations
Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge (2011) — 492 citations
NiftyNet: a deep-learning platform for medical imaging (2017) — 565 citations
Weakly-supervised convolutional neural networks for multimodal image registration (2018) — 442 citations
Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks (2018) — 730 citations
MONAI: An open-source framework for deep learning in healthcare (2022) — 996 citations
CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation (2020) — 655 citations
Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning (2017) — 764 citations
On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task (2017) — 364 citations
Intraoperative Organ Motion Models with an Ensemble of Conditional Generative Adversarial Networks (2017) — 16 citations
Diffeomorphic demons: Efficient non-parametric image registration (2009) — 1,723 citations
Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration (2009) — 2,380 citations
Spherical Demons: Fast Diffeomorphic Landmark-Free Surface Registration (2009) — 360 citations
Non-parametric Diffeomorphic Image Registration with the Demons Algorithm (2007) — 456 citations