Volker Fischer

Artificial Intelligence · with Metzen · 2016–2017

A researcher in the Science corpus: 4 papers; trusts 293 researchers and is trusted by 35 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 45 citations into it; #6,208 of 35,345 by trust here, #5,495 by citations
• Computer Vision and Pattern Recognition — 43 citations into it
• Safety, Robustness & Interpretability — 29 citations into it; #442 of 2,251 by trust here, #468 by citations
• Model Architectures — 10 citations into it
• Signal Processing — 7 citations into it
• Hardware and Architecture — 5 citations into it

Whom Volker Fischer trusts overall

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

1. Ian J. Goodfellow
2. Christian Szegedy
3. Karen Simonyan
4. Alex Krizhevsky
5. Geoffrey E. Hinton
6. Kaiming He
7. Ross B. Girshick
8. Diederik P. Kingma
9. Ilya Sutskever
10. Evan Shelhamer

Who trusts Volker Fischer overall

1. Nicholas Carlini
2. Jan Hendrik Metzen
3. Cihang Xie
4. Xiaojun Xu
5. Vikash Sehwag
6. Mahmood Sharif
7. Edward Chou
8. Eric Wong
9. Dan Hendrycks
10. Tianyu Pang

Papers from Volker Fischer's perspective

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

Their papers

• On Detecting Adversarial Perturbations (2017) — 1,037 citations
• Universal Adversarial Perturbations Against Semantic Image Segmentation (2017) — 309 citations
• Adversarial Examples for Semantic Image Segmentation (2017) — 123 citations
• Multispectral Pedestrian Detection using Deep Fusion Convolutional Neural Networks (2016) — 298 citations