Nima Hatami

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 13 citations into it
• Signal Processing — 10 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it

Whom Nima Hatami trusts overall

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

1. Yann LeCun
2. Geoffrey E. Hinton
3. Ossama Abdel-Hamid
4. Jessica Lin
5. L. Eon Bottou
6. Wenling Shang
7. Yangqing Jia
8. Alex Krizhevsky
9. Abdel-rahman Mohamed
10. Jianbo Yang

Who trusts Nima Hatami overall

1. Erico Tjoa
2. Hassan Ismail Fawaz
3. Cuntai Guan
4. François Soumis
5. Germain Forestier
6. Marc Rußwurm

Papers from Nima Hatami's perspective

Ordered by how strongly the researchers Nima Hatami 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Magnetic Resonance Spectroscopy Quantification using Deep Learning (2018) — 48 citations
• Classification of time-series images using deep convolutional neural networks (2017) — 391 citations