Paul-Gerhard Plöger

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 10 citations into it
• Artificial Intelligence — 8 citations into it
• Model Architectures — 6 citations into it

Whom Paul-Gerhard Plöger trusts overall

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

1. Diederik P. Kingma
2. Yichuan Tang
3. François Chollet
4. Sergey Ioffe
5. Kaiming He
6. Geoffrey E. Hinton
7. Christian Szegedy
8. Yoshua Bengio
9. Xavier Glorot
10. Alex Krizhevsky

Papers from Paul-Gerhard Plöger's perspective

Ordered by how strongly the researchers Paul-Gerhard Plöger 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Real-time Convolutional Neural Networks for emotion and gender classification (2017) — 317 citations