Boudewijn P. F. Lelieveldt

Computer Vision and Pattern Recognition · 2001–2021

A researcher in the Science corpus: 13 papers; trusts 39 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 78 citations into it; #9,409 of 21,575 by trust here, #6,426 by citations
• Artificial Intelligence — 32 citations into it; #25,760 of 35,345 by trust here, #20,377 by citations
• Radiology, Nuclear Medicine and Imaging — 22 citations into it
• Representation & Self-Supervised Learning — 22 citations into it
• Signal Processing — 12 citations into it
• Information Retrieval & Search — 6 citations into it
• Astronomy and Astrophysics — 5 citations into it

Whom Boudewijn P. F. Lelieveldt trusts overall

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

1. L. V. D. van der Maaten
2. Geoffrey E. Hinton
3. Yann LeCun
4. Marius Muja
5. David G. Lowe
6. Alex Krizhevsky
7. Josh Tenenbaum
8. Vin de Silva
9. Yoshua Bengio
10. Sam T. Roweis

Who trusts Boudewijn P. F. Lelieveldt overall

1. Alexander Andreopoulos
2. Nicola Pezzotti
3. Alison Noble
4. Anna C. Belkina
5. Kang Li
6. Caroline Petitjean
7. John K. Tsotsos
8. Thomas Höllt
9. David Chan
10. J. Bosch

Papers from Boudewijn P. F. Lelieveldt's perspective

Ordered by how strongly the researchers Boudewijn P. F. Lelieveldt 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Nonrigid Image Registration Using Multi-scale 3D Convolutional Neural Networks (2017) — 424 citations
• Eleven grand challenges in single-cell data science (2020) — 1,198 citations
• An Objective Comparison of Cell Tracking Algorithms (2017) — 542 citations
• Visual analysis of mass cytometry data by hierarchical stochastic neighbour embedding reveals rare cell types (2017) — 208 citations
• 3-D active appearance models: segmentation of cardiac MR and ultrasound images (2002) — 465 citations
• Conserved cell types with divergent features in human versus mouse cortex (2019) — 1,546 citations
• Comparative cellular analysis of motor cortex in human, marmoset and mouse (2021) — 639 citations
• Fast parallel image registration on CPU and GPU for diagnostic classification of Alzheimer's disease (2013) — 614 citations
• Linear tSNE optimization for the Web (2018) — 10 citations
• Hierarchical Stochastic Neighbor Embedding (2016) — 152 citations
• Approximated and User Steerable tSNE for Progressive Visual Analytics (2015) — 303 citations
• Automatic segmentation of echocardiographic sequences by active appearance motion models (2002) — 340 citations
• Multistage hybrid active appearance model matching: segmentation of left and right ventricles in cardiac MR images (2001) — 393 citations