Amir Erfan Eshratifar

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 3 papers; trusts 259 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 50 citations into it; #11,614 of 21,575 by trust here, #16,367 by citations
• Artificial Intelligence — 29 citations into it
• Model Architectures — 10 citations into it
• Optimization & Training — 6 citations into it
• Representation & Self-Supervised Learning — 6 citations into it
• Generative Models — 5 citations into it

Whom Amir Erfan Eshratifar trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Karen Simonyan
5. Christian Szegedy
6. Ilya Sutskever
7. Yoshua Bengio
8. Yann LeCun
9. Diederik P. Kingma
10. Ross B. Girshick

Who trusts Amir Erfan Eshratifar overall

1. Young Geun Kim
2. Carole-Jean Wu
3. Zecheng He
4. Mingzhe Chen
5. Yoshitomo Matsubara
6. Tianwei Zhang
7. Deniz Gündüz
8. Jun Shu

Papers from Amir Erfan Eshratifar's perspective

Ordered by how strongly the researchers Amir Erfan Eshratifar 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
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

• Coarse2Fine: a two-stage training method for fine-grained visual classification (2019) — 13 citations
• Gradient Agreement as an Optimization Objective for Meta-Learning (2018) — 16 citations
• JointDNN: An Efficient Training and Inference Engine for Intelligent Mobile Cloud Computing Services (2018) — 305 citations