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ORCIDSvetlana Pavlitska
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- affiliation: FZI Forschungszentrum Informatik, KIT, Karlsruhe, Germany
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Conference and Workshop Papers
- 2023
[c15]Svetlana Pavlitska, Christian Hubschneider, Lukas Struppek, J. Marius Zöllner:
Sparsely-gated Mixture-of-Expert Layers for CNN Interpretability. IJCNN 2023: 1-10- [c14]Tobias Fleck, Svetlana Pavlitska, Sven Nitzsche, Brian Pachideh, Federico Nicolás Peccia, Soikat Hasan Ahmed, Svea Marie Meyer, Mathis Richter, Kevin Broertjes, Emre Neftci, Jürgen Becker, Oliver Bringmann, J. Marius Zöllner:
Low-Power Traffic Surveillance using Multiple RGB and Event Cameras: A Survey. ISC2 2023: 1-7 - [c13]Svetlana Pavlitska, Nico Lambing, Ashok Kumar Bangaru, J. Marius Zöllner:
Traffic Light Recognition using Convolutional Neural Networks: A Survey. ITSC 2023: 2790-2796 - [c12]Svetlana Pavlitska, Hannes Grolig, J. Marius Zoellner:
Relationship between Model Compression and Adversarial Robustness: A Review of Current Evidence. SSCI 2023: 671-676 - [c11]Daniel Bogdoll, Svetlana Pavlitska, Simon Klaus, J. Marius Zöllner:
Conditioning Latent-Space Clusters for Real-World Anomaly Classification. SSCI 2023: 1620-1625 - 2022
- [c10]Svetlana Pavlitskaya, Siyar Yikmis, J. Marius Zöllner:
Is Neuron Coverage Needed to Make Person Detection More Robust? CVPR Workshops 2022: 2888-2896 - [c9]Svetlana Pavlitskaya, Nikolai Polley, Michael Weber, J. Marius Zöllner:
Adversarial Vulnerability of Temporal Feature Networks for Object Detection. ECCV Workshops (5) 2022: 510-525 - [c8]Svetlana Pavlitskaya, Bianca-Marina Codau, J. Marius Zöllner:
Feasibility of Inconspicuous GAN-generated Adversarial Patches against Object Detection. AISafety@IJCAI 2022 - [c7]Helen Gremmelmaier, Lars Töttel, Svetlana Pavlitskaya, Stefan Orf, Marc Rene Zofka, J. Marius Zöllner:
Getting Ready for all Types of Users: A Virtual Reality Training Center for Automated Vehicles. SSCI 2022: 77-85 - [c6]Svetlana Pavlitskaya, Joël Oswald, J. Marius Zöllner:
Measuring Overfitting in Convolutional Neural Networks using Adversarial Perturbations and Label Noise. SSCI 2022: 1551-1559 - 2021
- [c5]Atanas Tanev, Svetlana Pavlitskaya, Joan Sigloch, Arne Roennau, Rüdiger Dillmann, J. Marius Zöllner:
Adversarial Black-Box Attacks on Vision-based Deep Reinforcement Learning Agents. ISR 2021: 177-181 - 2020
- [c4]Svetlana Pavlitskaya, Christian Hubschneider, Michael Weber, Ruby Moritz, Fabian Hüger, Peter Schlicht, J. Marius Zöllner:
Using Mixture of Expert Models to Gain Insights into Semantic Segmentation. CVPR Workshops 2020: 1399-1406 - [c3]Svetlana Pavlitskaya, Sefa Ünver, J. Marius Zöllner:
Feasibility and Suppression of Adversarial Patch Attacks on End-to-End Vehicle Control. ITSC 2020: 1-8 - 2019
- [c2]Evgeny Kusmenko, Svetlana Pavlitskaya, Bernhard Rumpe
, Sebastian Stüber:
On the Engineering of AI-Powered Systems. ASE Workshops 2019: 126-133 - [c1]Evgeny Kusmenko, Sebastian Nickels, Svetlana Pavlitskaya, Bernhard Rumpe, Thomas Timmermanns:
Modeling and Training of Neural Processing Systems. MoDELS 2019: 283-293
Informal and Other Publications
- 2023
- [i11]Svetlana Pavlitska, Nico Lambing, J. Marius Zöllner:
Adversarial Attacks on Traffic Sign Recognition: A Survey. CoRR abs/2307.08278 (2023) - [i10]Svetlana Pavlitska, Nico Lambing, Ashok Kumar Bangaru, J. Marius Zöllner:
Traffic Light Recognition using Convolutional Neural Networks: A Survey. CoRR abs/2309.02158 (2023) - [i9]Daniel Bogdoll, Svetlana Pavlitska, Simon Klaus, J. Marius Zöllner:
Conditioning Latent-Space Clusters for Real-World Anomaly Classification. CoRR abs/2309.09676 (2023) - [i8]Svetlana Pavlitska, Hannes Grolig, J. Marius Zöllner:
Relationship between Model Compression and Adversarial Robustness: A Review of Current Evidence. CoRR abs/2311.15782 (2023) - 2022
- [i7]Svetlana Pavlitskaya, Siyar Yikmis, J. Marius Zöllner:
Is Neuron Coverage Needed to Make Person Detection More Robust? CoRR abs/2204.10027 (2022) - [i6]Svetlana Pavlitskaya, Christian Hubschneider, Lukas Struppek, J. Marius Zöllner:
Balancing Expert Utilization in Mixture-of-Experts Layers Embedded in CNNs. CoRR abs/2204.10598 (2022) - [i5]Svetlana Pavlitskaya, Bianca-Marina Codau, J. Marius Zöllner:
Feasibility of Inconspicuous GAN-generated Adversarial Patches against Object Detection. CoRR abs/2207.07347 (2022) - [i4]Svetlana Pavlitskaya, Nikolai Polley, Michael Weber, J. Marius Zöllner:
Adversarial Vulnerability of Temporal Feature Networks for Object Detection. CoRR abs/2208.10773 (2022) - [i3]Svetlana Pavlitskaya, Jonas Hendl, Sebastian Kleim, Leopold Müller, Fabian Wylczoch, J. Marius Zöllner:
Suppress with a Patch: Revisiting Universal Adversarial Patch Attacks against Object Detection. CoRR abs/2209.13353 (2022) - [i2]Svetlana Pavlitskaya, Joël Oswald, J. Marius Zöllner:
Measuring Overfitting in Convolutional Neural Networks using Adversarial Perturbations and Label Noise. CoRR abs/2209.13382 (2022) - 2021
- [i1]Sebastian Houben, Stephanie Abrecht, Maram Akila, Andreas Bär, Felix Brockherde, Patrick Feifel, Tim Fingscheidt, Sujan Sai Gannamaneni, Seyed Eghbal Ghobadi, Ahmed Hammam, Anselm Haselhoff, Felix Hauser, Christian Heinzemann, Marco Hoffmann, Nikhil Kapoor, Falk Kappel, Marvin Klingner, Jan Kronenberger, Fabian Küppers, Jonas Löhdefink, Michael Mlynarski, Michael Mock, Firas Mualla, Svetlana Pavlitskaya, Maximilian Poretschkin, Alexander Pohl, Varun Ravi Kumar, Julia Rosenzweig, Matthias Rottmann, Stefan Rüping, Timo Sämann, Jan David Schneider, Elena Schulz, Gesina Schwalbe, Joachim Sicking, Toshika Srivastava, Serin Varghese, Michael Weber, Sebastian Wirkert, Tim Wirtz, Matthias Woehrle:
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety. CoRR abs/2104.14235 (2021)
Coauthor Index
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