David Hurych

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 2 papers; trusts 123 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 59 citations into it
• Generative Models — 34 citations into it
• Artificial Intelligence — 32 citations into it
• Safety, Robustness & Interpretability — 10 citations into it
• Signal Processing — 7 citations into it

Whom David Hurych trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Ilya Sutskever
5. Yoshua Bengio
6. Ross B. Girshick
7. Kaiming He
8. Kexin Pei
9. Christian Szegedy
10. Ian J. Goodfellow

Papers from David Hurych's perspective

Ordered by how strongly the researchers David Hurych 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. ImageNet: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. ImageNet Large Scale Visual Recognition Challenge
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Challenges in Designing Datasets and Validation for Autonomous Driving (2019) — 40 citations
• Yes, we GAN: Applying Adversarial Techniques for Autonomous Driving (2019) — 60 citations