Mohammad Sadegh Ali Akbarian

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 141 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 42 citations into it; #17,465 of 21,575 by trust here, #16,367 by citations
• Artificial Intelligence — 23 citations into it; #28,511 of 35,345 by trust here, #25,040 by citations
• Biomedical Engineering — 7 citations into it

Whom Mohammad Sadegh Ali Akbarian trusts overall

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

1. Karen Simonyan
2. Andrew Zisserman
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Kaiming He
6. Ross B. Girshick
7. Yoshua Bengio
8. Yann LeCun
9. Michael S. Ryoo
10. Diederik P. Kingma

Who trusts Mohammad Sadegh Ali Akbarian overall

1. Antonino Furnari
2. Giovanni Maria Farinella
3. Yazan Abu Farha
4. Lukás Neumann
5. Ivan Rodin
6. Qiuhong Ke
7. Andrew Zisserman
8. Alexander Richard

Papers from Mohammad Sadegh Ali Akbarian's perspective

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

Their papers

• Encouraging LSTMs to Anticipate Actions Very Early (2017) — 181 citations