Jelmer M. Wolterink

Computer Vision and Pattern Recognition · 2016–2019

A researcher in the Science corpus: 5 papers; trusts 35 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 48 citations into it; #17,551 of 21,575 by trust here, #8,205 by citations
• Artificial Intelligence — 23 citations into it
• Generative Models — 14 citations into it
• Optimization & Training — 9 citations into it

Whom Jelmer M. Wolterink trusts overall

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

1. Diederik P. Kingma
2. Jimmy Ba
3. Phillip Isola
4. Yoshua Bengio
5. Geoffrey E. Hinton
6. Alex Krizhevsky
7. Xavier Glorot
8. Karen Simonyan
9. Jun-Yan Zhu
10. Yann LeCun

Who trusts Jelmer M. Wolterink overall

1. Xin Yi
2. Faisal Mahmood
3. Sergey I. Nikolenko
4. Arvid Lundervold
5. Martin J. Willemink
6. Karim Armanious
7. Paul S. Babyn
8. Richard J. Chen
9. Onat Dalmaz
10. Joseph Paul Cohen

Papers from Jelmer M. Wolterink's perspective

Ordered by how strongly the researchers Jelmer M. Wolterink 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. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Long Short-Term Memory
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Generative Adversarial Networks for Noise Reduction in Low-Dose CT (2017) — 915 citations
• State-of-the-Art Deep Learning in Cardiovascular Image Analysis. (2019) — 352 citations
• Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved? (2018) — 2,285 citations
• Deep MR to CT Synthesis Using Unpaired Data (2017) — 681 citations
• Deep Learning for Multi-Task Medical Image Segmentation in Multiple Modalities (2016) — 339 citations