Nicolas Bourdis

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 33 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 22 citations into it; #17,978 of 21,575 by trust here, #15,955 by citations
• Electrical and Electronic Engineering — 19 citations into it; #12,092 of 16,539 by trust here, #11,641 by citations
• Artificial Intelligence — 10 citations into it
• Cognitive Neuroscience — 9 citations into it
• Cellular and Molecular Neuroscience — 8 citations into it

Whom Nicolas Bourdis trusts overall

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

1. Alex Krizhevsky
2. Yann LeCun
3. Geoffrey E. Hinton
4. Navneet Dalal
5. Tom Fawcett
6. Daniel Neil
7. Kaiming He
8. David G. Lowe
9. Garrick Orchard
10. Shaoqing Ren

Who trusts Nicolas Bourdis overall

1. Henri Rebecq

Papers from Nicolas Bourdis's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Learning Multiple Layers of Features from Tiny Images
7. Histograms of oriented gradients for human detection
8. Long Short-Term Memory
9. Dropout: a simple way to prevent neural networks from overfitting
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• HATS: Histograms of Averaged Time Surfaces for Robust Event-Based Object Classification (2018) — 552 citations