Fabian Gieseke

Computer Vision and Pattern Recognition · 2014–2020

A researcher in the Science corpus: 2 papers; trusts 130 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 54 citations into it
• Artificial Intelligence — 41 citations into it
• Model Architectures — 23 citations into it
• Representation & Self-Supervised Learning — 6 citations into it
• Statistical Learning Theory — 5 citations into it
• Optimization & Training — 5 citations into it

Whom Fabian Gieseke trusts overall

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

1. Christopher K. I. Williams
2. Olivier Chapelle
3. Thorsten Joachims
4. Alex Krizhevsky
5. Kaiming He
6. Chih-Jen Lin
7. Geoffrey E. Hinton
8. Ross B. Girshick
9. Bernhard Schölkopf
10. Yoshua Bengio

Who trusts Fabian Gieseke overall

1. Julius von Kügelgen
2. Sheng Fang
3. Marco Loog

Papers from Fabian Gieseke's perspective

Ordered by how strongly the researchers Fabian Gieseke 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Going deeper with convolutions
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Fast and simple gradient-based optimization for semi-supervised support vector machines (2014) — 60 citations
• Attentional Feature Fusion (2020) — 979 citations