Mohamed El Amine Seddik

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 172 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 46 citations into it; #18,169 of 21,575 by trust here, #20,756 by citations
• Artificial Intelligence — 36 citations into it; #29,556 of 35,345 by trust here, #33,294 by citations
• Model Architectures — 5 citations into it
• Optimization & Training — 5 citations into it

Whom Mohamed El Amine Seddik trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Karen Simonyan
4. Yoshua Bengio
5. Kaiming He
6. Ilya Sutskever
7. Andrew Zisserman
8. Yann LeCun
9. Diederik P. Kingma
10. Rob Fergus

Who trusts Mohamed El Amine Seddik overall

1. Eden Belouadah

Papers from Mohamed El Amine Seddik's perspective

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

Their papers

• Learning More Universal Representations for Transfer-Learning (2017) — 60 citations