E
Evgenia Rusak
Researcher at Karlsruhe Institute of Technology
Publications - 24
Citations - 1417
Evgenia Rusak is an academic researcher from Karlsruhe Institute of Technology. The author has contributed to research in topics: Spontaneous emission & Dipole. The author has an hindex of 12, co-authored 20 publications receiving 928 citations. Previous affiliations of Evgenia Rusak include Australian National University & University of Tübingen.
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Active Tuning of All-Dielectric Metasurfaces
Jürgen Sautter,Isabelle Staude,Manuel Decker,Evgenia Rusak,Dragomir N. Neshev,Igal Brener,Yuri S. Kivshar +6 more
TL;DR: Dynamic tuning of electric and magnetic resonances in all-dielectric silicon nanodisk metasurfaces in the telecom spectral range based on the temperature-dependent refractive-index change of a nematic liquid crystal is experimentally demonstrated.
Posted Content
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
Claudio Michaelis,Benjamin Mitzkus,Robert Geirhos,Evgenia Rusak,Oliver Bringmann,Alexander S. Ecker,Matthias Bethge,Wieland Brendel +7 more
TL;DR: It is shown that a range of standard object detection models suffer a severe performance loss on corrupted images (down to 30--60\% of the original performance), however, a simple data augmentation trick---stylizing the training images---leads to a substantial increase in robustness across corruption type, severity and dataset.
Posted Content
Improving robustness against common corruptions by covariate shift adaptation
TL;DR: It is argued that results with adapted statistics should be included whenever reporting scores in corruption benchmarks and other out-of-distribution generalization settings, and 32 samples are sufficient to improve the current state of the art for a ResNet-50 architecture.
Posted Content
A simple way to make neural networks robust against diverse image corruptions
Evgenia Rusak,Lukas Schott,Roland S. Zimmermann,Julian Bitterwolf,Oliver Bringmann,Matthias Bethge,Wieland Brendel +6 more
TL;DR: It is demonstrated that a simple but properly tuned training with additive Gaussian and Speckle noise generalizes surprisingly well to unseen corruptions, easily reaching the previous state of the art on the corruption benchmark ImageNet-C (with ResNet50) and on MNIST-C.
Journal ArticleDOI
Hybrid nanoantennas for directional emission enhancement
Evgenia Rusak,Isabelle Staude,Manuel Decker,Jürgen Sautter,Andrey E. Miroshnichenko,David A. Powell,Dragomir N. Neshev,Yuri S. Kivshar +7 more
TL;DR: In this article, a hybrid metal-dielectric nano-antenna consisting of a gold nanorod and a silicon nanodisk was proposed to achieve a giant enhancement of directional emission together with simultaneously high radiation efficiency.