Gertjan J. Burghouts

Computer Vision and Pattern Recognition · 2004–2024

A researcher in the Science corpus: 6 papers; trusts 438 researchers and is trusted by 26 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 118 citations into it; #5,508 of 21,575 by trust here, #9,079 by citations
• Artificial Intelligence — 88 citations into it
• Model Architectures — 26 citations into it
• Optimization & Training — 16 citations into it
• Aerospace Engineering — 13 citations into it
• Representation & Self-Supervised Learning — 13 citations into it
• Natural Language Processing — 12 citations into it
• Generative Models — 10 citations into it

Whom Gertjan J. Burghouts trusts overall

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

1. Radford M. Neal
2. Geoffrey E. Hinton
3. Kaiming He
4. Diederik P. Kingma
5. Alex Krizhevsky
6. Yann LeCun
7. Yoshua Bengio
8. Andrew Zisserman
9. Ilya Sutskever
10. David G. Lowe

Who trusts Gertjan J. Burghouts overall

1. Christian Beecks
2. Matthew A. Brown
3. Sabine Süsstrunk
4. Haonan Yu
5. Tony Lindeberg
6. K. V. D. Sande
7. Alaa E. Abdel-Hakim
8. Yichuan Tang
9. Markus Goldstein
10. Cees G. M. Snoek

Papers from Gertjan J. Burghouts's perspective

Ordered by how strongly the researchers Gertjan J. Burghouts 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. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
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

• The Amsterdam Library of Object Images (2004) — 1,004 citations
• Automated Textual Descriptions for a Wide Range of Video Events with 48 Human Actions (2012) — 47 citations
• Performance evaluation of local colour invariants (2009) — 351 citations
• Set Prediction without Imposing Structure as Conditional Density Estimation (2020) — 19 citations
• Better Language Models Exhibit Higher Visual Alignment (2024)
• Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation (2021) — 22 citations