Léopold Cambier

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 16 citations into it
• Artificial Intelligence — 15 citations into it

Whom Léopold Cambier trusts overall

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

1. Diederik P. Kingma
2. Kaiming He
3. Yann LeCun
4. Yunhui Guo
5. Ashish Vaswani
6. Alex Krizhevsky
7. Geoffrey E. Hinton
8. Yoshua Bengio
9. Jia Deng
10. Jimmy Ba

Papers from Léopold Cambier's perspective

Ordered by how strongly the researchers Léopold Cambier 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. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Shifted and Squeezed 8-bit Floating Point format for Low-Precision Training of Deep Neural Networks (2020) — 54 citations