Tim Leiner

Computer Vision and Pattern Recognition · 2016–2019

A researcher in the Science corpus: 3 papers; trusts 15 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 32 citations into it
• Artificial Intelligence — 19 citations into it
• Optimization & Training — 8 citations into it

Whom Tim Leiner trusts overall

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

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

Who trusts Tim Leiner overall

1. Xin Yi
2. Martin J. Willemink
3. Faisal Mahmood
4. Paul S. Babyn
5. Tao Zhou

Papers from Tim Leiner's perspective

Ordered by how strongly the researchers Tim Leiner trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
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 for Multi-Task Medical Image Segmentation in Multiple Modalities (2016) — 339 citations