Viktor Seib

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 32 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 33 citations into it
• Artificial Intelligence — 23 citations into it
• Control and Systems Engineering — 15 citations into it
• Reinforcement Learning — 9 citations into it
• Aerospace Engineering — 8 citations into it
• Robotics & Control — 8 citations into it

Whom Viktor Seib trusts overall

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

1. Kaiming He
2. Jonathan Ho
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Ross B. Girshick
6. Nathan P. Koenig
7. Tanmay Gangwani

Papers from Viktor Seib's perspective

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

Their papers

• Simitate: A Hybrid Imitation Learning Benchmark (2019) — 20 citations