Ralph Ewerth

Computer Vision and Pattern Recognition · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 364 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 47 citations into it
• Artificial Intelligence — 18 citations into it
• Aerospace Engineering — 15 citations into it
• Multimodal Learning — 11 citations into it
• Evaluation & Benchmarks — 6 citations into it
• Media Technology — 6 citations into it
• Natural Language Processing — 6 citations into it

Whom Ralph Ewerth trusts overall

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

1. Kaiming He
2. Oriol Vinyals
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Ilya Sutskever
6. Karen Simonyan
7. Christian Szegedy
8. Yoshua Bengio
9. James Hays
10. Andrew Zisserman

Papers from Ralph Ewerth's perspective

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

Their papers

• Geolocation Estimation of Photos Using a Hierarchical Model and Scene Classification (2018) — 126 citations
• Estimating the information gap between textual and visual representations (2017) — 33 citations