activity
20232025
most citedHow Could Generative AI Support Compliance with the EU AI Act? A Review for Safe Automated Driving Perception

5 citations · 6 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2025

Following the Clues: Experiments on Person Re-ID using Cross-Modal Intelligence

Robert Aufschläger, Youssef Shoeb, Azarm Nowzad +3

The collection and release of street-level recordings as Open Data play a vital role in advancing autonomous driving systems and AI research. However, these datasets pose significa…

cs.CV2025

Out-of-Distribution Segmentation in Autonomous Driving: Problems and State of the Art

Youssef Shoeb, Azarm Nowzad, Hanno Gottschalk

In this paper, we review the state of the art in Out-of-Distribution (OoD) segmentation, with a focus on road obstacle detection in automated driving as a real-world application. W…

cs.CV2025

Adaptive Neural Networks for Intelligent Data-Driven Development

Youssef Shoeb, Azarm Nowzad, Hanno Gottschalk

Advances in machine learning methods for computer vision tasks have led to their consideration for safety-critical applications like autonomous driving. However, effectively integr…

cs.CV2024★ 1 cited

Segment-Level Road Obstacle Detection Using Visual Foundation Model Priors and Likelihood Ratios

Youssef Shoeb, Nazir Nayal, Azarm Nowzad +2

Detecting road obstacles is essential for autonomous vehicles to navigate dynamic and complex traffic environments safely. Current road obstacle detection methods typically assign…

cs.CV2024

A Likelihood Ratio-Based Approach to Segmenting Unknown Objects

Nazir Nayal, Youssef Shoeb, Fatma Güney

Addressing the Out-of-Distribution (OoD) segmentation task is a prerequisite for perception systems operating in an open-world environment. Large foundational models are frequently…

cs.CV2024★ 5 cited

How Could Generative AI Support Compliance with the EU AI Act? A Review for Safe Automated Driving Perception

Mert Keser, Youssef Shoeb, Alois Knoll

Deep Neural Networks (DNNs) have become central for the perception functions of autonomous vehicles, substantially enhancing their ability to understand and interpret the environme…

cs.CV2023

Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles from Driving Scenes

Youssef Shoeb, Robin Chan, Gesina Schwalbe +3

In the life cycle of highly automated systems operating in an open and dynamic environment, the ability to adjust to emerging challenges is crucial. For systems integrating data-dr…