Ehsan Kazemi

Artificial Intelligence · 2017–2020

A researcher in the Science corpus: 3 papers; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 36 citations into it
• Computer Vision and Pattern Recognition — 32 citations into it
• Computational Theory and Mathematics — 13 citations into it
• Model Architectures — 12 citations into it

Whom Ehsan Kazemi trusts overall

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

1. Christian Szegedy
2. Yann LeCun
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Kaiming He
6. Karen Simonyan
7. Yoshua Bengio
8. Ilya Sutskever
9. L. Eon Bottou
10. Andrew Zisserman

Papers from Ehsan Kazemi's perspective

Ordered by how strongly the researchers Ehsan Kazemi 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. ImageNet Large Scale Visual Recognition Challenge
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Going deeper with convolutions
7. ImageNet: A large-scale hierarchical image database
8. Long Short-Term Memory
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Submodular Maximization in Clean Linear Time (2020) — 27 citations
• Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization (2019) — 370 citations
• Deep Convolutional Neural Networks Enable Discrimination of Heterogeneous Digital Pathology Images (2017) — 314 citations