Etienne Perot

Computer Vision and Pattern Recognition · 2016–2020

A researcher in the Science corpus: 3 papers; trusts 78 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 37 citations into it
• Artificial Intelligence — 36 citations into it; #13,235 of 35,345 by trust here, #12,083 by citations
• Reinforcement Learning — 23 citations into it; #1,487 of 2,242 by trust here, #1,344 by citations
• Electrical and Electronic Engineering — 20 citations into it
• Cognitive Neuroscience — 16 citations into it
• Model Architectures — 11 citations into it

Whom Etienne Perot trusts overall

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

1. Richard S. Sutton
2. Kaiming He
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. Ronald J. Williams
6. Paul J. Werbos
7. Alex Krizhevsky
8. Tsung-Yi Lin
9. Yoshua Bengio
10. Volodymyr Mnih

Who trusts Etienne Perot overall

1. Sergey I. Nikolenko
2. Edouard Leurent
3. Praveen Palanisamy
4. Shansi Zhang
5. Krzysztof Czarnecki
6. Pin Wang
7. Ammar Haydari

Papers from Etienne Perot's perspective

Ordered by how strongly the researchers Etienne Perot trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
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. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet Large Scale Visual Recognition Challenge
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Deep Reinforcement Learning framework for Autonomous Driving (2017) — 1,062 citations
• Learning to Detect Objects with a 1 Megapixel Event Camera (2020) — 351 citations
• End-to-End Deep Reinforcement Learning for Lane Keeping Assist (2016) — 184 citations