Axel Saalbach

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 30 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 19 citations into it
• Artificial Intelligence — 16 citations into it
• Model Architectures — 7 citations into it
• Optimization & Training — 5 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Axel Saalbach trusts overall

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

1. R. Caruana
2. Kaiming He
3. Gao Huang
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. David Lopez-Paz
7. Yoshua Bengio
8. Pranav Rajpurkar
9. Marc'Aurelio Ranzato
10. X. Zhang

Papers from Axel Saalbach's perspective

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

Their papers

• Continual Learning for Domain Adaptation in Chest X-ray Classification (2020) — 72 citations
• Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification (2018) — 438 citations