On the Engineering of AI-Powered Systems. - Evgeny Kusmenko; Svetlana Pavlitskaya; Bernhard Rumpe; Sebastian Stüber (ASE Workshops, 2019)

Modeling and Training of Neural Processing Systems. - Evgeny Kusmenko; Sebastian Nickels; Svetlana Pavlitskaya; Bernhard Rumpe; Thomas Timmermanns (MoDELS, 2019)

Using Mixture of Expert Models to Gain Insights into Semantic Segmentation. - Svetlana Pavlitskaya; Christian Hubschneider; Michael Weber 009; Ruby Moritz; Fabian Hüger; Peter Schlicht; J. Marius Zöllner (CVPR Workshops, 2020)

Feasibility and Suppression of Adversarial Patch Attacks on End-to-End Vehicle Control. - Svetlana Pavlitskaya; Sefa Ünver; J. Marius Zöllner (ITSC, 2020)

Adversarial Black-Box Attacks on Vision-based Deep Reinforcement Learning Agents. - Atanas Tanev; Svetlana Pavlitskaya; Joan Sigloch; Arne Roennau; Rüdiger Dillmann; J. Marius Zöllner (ISR, 2021)

Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety. - 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; et al. (CoRR, 2021)

Is Neuron Coverage Needed to Make Person Detection More Robust? - Svetlana Pavlitskaya; Siyar Yikmis; J. Marius Zöllner (CVPR Workshops, 2022)

Adversarial Vulnerability of Temporal Feature Networks for Object Detection. - Svetlana Pavlitskaya; Nikolai Polley; Michael Weber 009; J. Marius Zöllner (ECCV Workshops (5), 2022)

Feasibility of Inconspicuous GAN-generated Adversarial Patches against Object Detection. - Svetlana Pavlitskaya; Bianca-Marina Codau; J. Marius Zöllner (AISafety@IJCAI, 2022)

Getting Ready for all Types of Users: A Virtual Reality Training Center for Automated Vehicles. - Helen Gremmelmaier; Lars Töttel; Svetlana Pavlitskaya; Stefan Orf; Marc Rene Zofka; J. Marius Zöllner (SSCI, 2022)

Measuring Overfitting in Convolutional Neural Networks using Adversarial Perturbations and Label Noise. - Svetlana Pavlitskaya; Joël Oswald; J. Marius Zöllner (SSCI, 2022)

Balancing Expert Utilization in Mixture-of-Experts Layers Embedded in CNNs. - Svetlana Pavlitskaya; Christian Hubschneider; Lukas Struppek; J. Marius Zöllner (CoRR, 2022)

Suppress with a Patch: Revisiting Universal Adversarial Patch Attacks against Object Detection. - Svetlana Pavlitskaya; Jonas Hendl; Sebastian Kleim; Leopold Müller; Fabian Wylczoch; J. Marius Zöllner (CoRR, 2022)

Sparsely-gated Mixture-of-Expert Layers for CNN Interpretability. - Svetlana Pavlitska; Christian Hubschneider; Lukas Struppek; J. Marius Zöllner (IJCNN, 2023)

Low-Power Traffic Surveillance using Multiple RGB and Event Cameras: A Survey. - 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 001; Oliver Bringmann 001; et al. (ISC2, 2023)

Traffic Light Recognition using Convolutional Neural Networks: A Survey. - Svetlana Pavlitska; Nico Lambing; Ashok Kumar Bangaru; J. Marius Zöllner (ITSC, 2023)

Conditioning Latent-Space Clusters for Real-World Anomaly Classification. - Daniel Bogdoll; Svetlana Pavlitska; Simon Klaus; J. Marius Zöllner (SSCI, 2023)

Relationship between Model Compression and Adversarial Robustness: A Review of Current Evidence. - Svetlana Pavlitska; Hannes Grolig; J. Marius Zoellner (SSCI, 2023)

Adversarial Attacks on Traffic Sign Recognition: A Survey. - Svetlana Pavlitska; Nico Lambing; J. Marius Zöllner (CoRR, 2023)

Hybrid Video Anomaly Detection for Autonomous Driving. - Daniel Bogdoll; Jan Imhof; Tim Joseph; Svetlana Pavlitska; J. Marius Zöllner (BMVC Workshops, 2024)

UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving. - Daniel Bogdoll; Noël Ollick; Tim Joseph; Svetlana Pavlitska; J. Marius Zöllner (BMVC Workshops, 2024)

CAGE: Circumplex Affect Guided Expression Inference. - Niklas Wagner; Felix Mätzler; Samed Rouven Vossberg; Helen Schneider; Svetlana Pavlitska; J. Marius Zöllner (CVPR Workshops, 2024)

Efficient Edge AI: Deploying Convolutional Neural Networks on FPGA with the Gemmini Accelerator. - Federico Nicolás Peccia; Svetlana Pavlitska; Tobias Fleck; Oliver Bringmann 001 (DSD, 2024)

Towards Adversarial Robustness of Model-Level Mixture-of-Experts Architectures for Semantic Segmentation. - Svetlana Pavlitska; Enrico Eisen; J. Marius Zöllner (ICMLA, 2024)

Evaluating Adversarial Attacks on Traffic Sign Classifiers Beyond Standard Baselines. - Svetlana Pavlitska; Leopold Müller; J. Marius Zöllner (ICMLA, 2024)

Iterative Filter Pruning for Concatenation-based CNN Architectures. - Svetlana Pavlitska; Oliver Bagge; Federico Nicolás Peccia; Toghrul Mammadov; J. Marius Zöllner (IJCNN, 2024)

TLD-READY: Traffic Light Detection - Relevance Estimation and Deployment Analysis. - Nikolai Polley; Svetlana Pavlitska; Yacin Boualili; Patrick Rohrbeck; Paul Stiller; Ashok Kumar Bangaru; Johann Marius Zöllner (ITSC, 2024)

One Stack to Rule them All: To Drive Automated Vehicles, and Reach for the 4th level. - Sven Ochs; Jens Doll; Daniel Grimm; Tobias Fleck; Marc Heinrich; Stefan Orf; Albert Schotschneider; Helen Gremmelmaier; Rupert Polley; Svetlana Pavlitska; Maximilian Zipfl; Helen Schneider; et al. (CoRR, 2024)

Complementary Learning for Real-World Model Failure Detection. - Daniel Bogdoll; Finn Sartoris; Vincent Geppert; Svetlana Pavlitska; J. Marius Zöllner (CoRR, 2024)

Datasets for Valence and Arousal Inference: A Survey. - Helen Schneider; Svetlana Pavlitska; Helen Gremmelmaier; Marius Zöllner 001 (CVPR Workshops, 2025)

Fool the Stoplight: Realistic Adversarial Patch Attacks on Traffic Light Detectors. - Svetlana Pavlitska; Jamie Robb; Nikolai Polley; Melih Yazgan; J. Marius Zöllner (CoRR, 2025)

Extracting Uncertainty Estimates from Mixtures of Experts for Semantic Segmentation. - Svetlana Pavlitska; Beyza Keskin; Alwin Faßbender; Christian Hubschneider; J. Marius Zöllner (CoRR, 2025)

Robust Experts: the Effect of Adversarial Training on CNNs with Sparse Mixture-of-Experts Layers. - Svetlana Pavlitska; Haixi Fan; Konstantin Ditschuneit; J. Marius Zöllner (CoRR, 2025)

DEAP DIVE: Dataset Investigation with Vision transformers for EEG evaluation. - Annemarie Hoffsommer; Helen Schneider; Svetlana Pavlitska; J. Marius Zöllner (CoRR, 2025)