Christian F. Baumgartner

Computer Vision and Pattern Recognition · 2016–2018

A researcher in the Science corpus: 5 papers; trusts 153 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 67 citations into it
• Artificial Intelligence — 42 citations into it
• Generative Models — 11 citations into it
• Optimization & Training — 6 citations into it
• Safety, Robustness & Interpretability — 6 citations into it

Whom Christian F. Baumgartner trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Karen Simonyan
4. Diederik P. Kingma
5. Jimmy Ba
6. Yann LeCun
7. Andrew Zisserman
8. Yoshua Bengio
9. L. Eon Bottou
10. Kaiming He

Who trusts Christian F. Baumgartner overall

1. Yuan Gao
2. Salome Kazeminia
3. S. Suganyadevi
4. Lisa M. Koch
5. Sergey I. Nikolenko
6. Berkman Sahiner
7. Geert J. S. Litjens
8. Alejandro Barredo Arrieta
9. J. Alison Noble
10. Christoph Baur

Papers from Christian F. Baumgartner's perspective

Ordered by how strongly the researchers Christian F. Baumgartner 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Visual Feature Attribution Using Wasserstein GANs (2017) — 158 citations
• Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved? (2018) — 2,285 citations
• SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound (2016) — 388 citations
• Real-Time Standard Scan Plane Detection and Localisation in Fetal Ultrasound Using Fully Convolutional Neural Networks (2016) — 69 citations
• Unsupervised domain adaptation in brain lesion segmentation with adversarial networks (2016) — 544 citations