Gregor Koehler

Computer Vision and Pattern Recognition · 2018–2023

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 35 citations into it
• Optimization & Training — 5 citations into it

Whom Gregor Koehler trusts overall

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

1. Kaiming He
2. Karen Simonyan
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Andrew Zisserman
6. Ilya Loshchilov
7. Diederik P. Kingma
8. Ross B. Girshick
9. Yoshua Bengio
10. Yuxin Wu

Papers from Gregor Koehler's perspective

Ordered by how strongly the researchers Gregor Koehler 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. Attention is All you Need (Neural Information Processing Systems)
4. ImageNet: A large-scale hierarchical image database
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. Long Short-Term Memory
10. Going deeper with convolutions

Their papers

• nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation (2018) — 1,100 citations
• MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation (2023) — 419 citations