Miguel Domínguez

Computer Vision and Pattern Recognition · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 121 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 61 citations into it
• Artificial Intelligence — 40 citations into it
• Graph Learning — 31 citations into it
• Model Architectures — 14 citations into it
• Optimization & Training — 6 citations into it

Whom Miguel Domínguez trusts overall

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

1. Karen Simonyan
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Sergey Ioffe
5. Diederik P. Kingma
6. Yann LeCun
7. Kaiming He
8. Yoshua Bengio
9. Jia Deng
10. Andrew Zisserman

Papers from Miguel Domínguez's perspective

Ordered by how strongly the researchers Miguel Domínguez 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• General-Purpose Deep Point Cloud Feature Extractor (2018) — 45 citations
• Robust Spatial Filtering With Graph Convolutional Neural Networks (2017) — 142 citations