Daniel Omeiza

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 43 citations into it
• Safety, Robustness & Interpretability — 27 citations into it
• Computer Vision and Pattern Recognition — 20 citations into it
• Human-Computer Interaction — 7 citations into it

Whom Daniel Omeiza trusts overall

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

1. Brian Y. Lim
2. Matthew D. Zeiler
3. Avanti Shrikumar
4. Rob Fergus
5. Jost Tobias Springenberg
6. Geoffrey E. Hinton
7. Danding Wang
8. Alex Krizhevsky
9. Richard S. Sutton
10. Sebastian Lapuschkin

Papers from Daniel Omeiza's perspective

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

Their papers

• Explanations in Autonomous Driving: A Survey (2021) — 340 citations