output
20122026
most citedA Survey on the Explainability of Supervised Machine Learning

984 citations

Showing 2025Show all

9 papers · 1 filter

cs.IT2025

OGC Geotech Interoperability Experiment Engineering Report

Mickaël Beaufils, Katharina Schleidt, Hylke van Der Schaaf +3

This Engineering Report (ER) describes the outcomes of the Open Geospatial Consortium (OGC) Geotech Interoperability Experiment (IE). The objective of this IE was to develop a comm…

cs.RO2025

From Real-World Traffic Data to Relevant Critical Scenarios

Florian Lüttner, Nicole Neis, Daniel Stadler +5

The reliable operation of autonomous vehicles, automated driving functions, and advanced driver assistance systems across a wide range of relevant scenarios is critical for their d…

cs.CV2025★ 1 cited

Measuring the Effect of Background on Classification and Feature Importance in Deep Learning for AV Perception

Anne Sielemann, Valentin Barner, Stefan Wolf +3

Common approaches to explainable AI (XAI) for deep learning focus on analyzing the importance of input features on the classification task in a given model: saliency methods like S…

cs.CV2025★ 3 cited

Synset Signset Germany: a Synthetic Dataset for German Traffic Sign Recognition

Anne Sielemann, Lena Loercher, Max-Lion Schumacher +3

In this paper, we present a synthesis pipeline and dataset for training / testing data in the task of traffic sign recognition that combines the advantages of data-driven and analy…

cs.RO2025★ 2 cited

Physically-Based Simulation of Automotive LiDAR

L. Dudzik, M. Roschani, A. Sielemann +4

We present an analytic model for simulating automotive time-of-flight (ToF) LiDAR that includes blooming, echo pulse width, and ambient light, along with steps to determine model p…

cs.GR2025

Efficient representation of 3D spatial data for defense-related applications

Benjamin Kahl, Marcus Hebel, Michael Arens

Geospatial sensor data is essential for modern defense and security, offering indispensable 3D information for situational awareness. This data, gathered from sources like lidar se…

cs.LG2025

Bayesian Optimization of Process Parameters of a Sensor-Based Sorting System using Gaussian Processes as Surrogate Models

Felix Kronenwett, Georg Maier, Thomas Längle

Sensor-based sorting systems enable the physical separation of a material stream into two fractions. The sorting decision is based on the image data evaluation of the sensors used…

astro-ph.IM2025★ 1 cited

Quantum-inspired exoplanet detection in the presence of experimental imperfections

Tomasz Linowski, Konrad Schlichtholz, Giacomo Sorelli

Ideal spatial demultiplexing (SPADE) is proven to be a quantum-optimal tool for exoplanet detection, i.e., asymmetric source discrimination. However, recent investigations into the…

cs.CV2025★ 2 cited

Polygonizing Roof Segments from High-Resolution Aerial Images Using Yolov8-Based Edge Detection

Qipeng Mei, Dimitri Bulatov, Dorota Iwaszczuk

This study presents a novel approach for roof detail extraction and vectorization using remote sensing images. Unlike previous geometric-primitive-based methods that rely on the de…