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1 to 10 of 33 Results
Socially Intelligent Robotics Lab(Universität Stuttgart)
Nov 3, 2025
AccessGuru
Sep 8, 2025 - IRIS 3D
Fathallah, Nadeen; Hernández, Daniel; Staab, Steffen, 2025, "AccessGuru", https://doi.org/10.18419/DARUS-5177, DaRUS, V1, UNF:6:5MctEb5nlHfFUXpoBqSNMg== [fileUNF]
AccessGuru dataset contains over 3,500 real-world Web accessibility violations collected from 448 diverse websites across domains such as health, education, government, news, technology, and e-commerce. Each instance is annotated with one of 112 distinct violation types, spanning syntactic, semantic, and layout categories as defined by WCAG 2.1 gui...
eSPARQL Implementation
Apr 28, 2025 - KR-Building (EXC IntCDC)
Pan, Xinyi; Hernández, Daniel; Seifer, Philipp; Lämmel, Ralf; Staab, Steffen, 2025, "eSPARQL Implementation", https://doi.org/10.18419/DARUS-4344, DaRUS, V1, UNF:6:t0V66ThHSAjSCe2jRbbJng== [fileUNF]
This project contains the code of an implementation of the eSPARQL language, which extends SPARQL-star with a `FROM BELIEF` that allows an easy formulation of epistemic queries. Further information can be found in the README.md file.
Code for Improving Video Caption Accuracy with LLMs
Feb 28, 2025 - Analytic Computing
Fathallah, Nadeen, 2025, "Code for Improving Video Caption Accuracy with LLMs", https://doi.org/10.18419/DARUS-4776, DaRUS, V1
As part of the IKILeUS project at the University of Stuttgart, research was conducted to explore how Large Language Models (LLMs) can enhance the accuracy and contextual relevance of automatic speech recognition (ASR)-generated captions. While ASR tools provide a foundation for accessibility, they often produce grammatical errors, misinterpret homo...
Code for Caption Crowd (IKILeUS)
Feb 28, 2025 - Analytic Computing
Fathallah, Nadeen; Staab, Steffen, 2025, "Code for Caption Crowd (IKILeUS)", https://doi.org/10.18419/DARUS-4775, DaRUS, V1, UNF:6:e9mxpfNAwwwZlt8Uc4I+mQ== [fileUNF]
CaptionCrowd is an interactive platform developed within the IKILeUS project at the University of Stuttgart to improve video caption accuracy for the Deaf and Hard of Hearing (DHH) community. While automatic captions provide some accessibility, they often contain errors in grammar, homophones, and domain-specific terminology, making comprehension c...
Code for EchoTables (IKILeUS)
Feb 28, 2025 - Analytic Computing
Fathallah, Nadeen; Staab, Steffen, 2025, "Code for EchoTables (IKILeUS)", https://doi.org/10.18419/DARUS-4774, DaRUS, V1
EchoTables is an innovative accessibility tool developed as part of the IKILeUS project at the University of Stuttgart. It is designed to improve the usability of tabular data for visually impaired users by converting structured tables into concise, auditory-friendly textual summaries. Traditional screen readers navigate tables linearly, which impo...
Code for statesim - a python package to simulate dynamical systems from ordinary differential equations.
Feb 26, 2025 - InMotion (EXC)
Frank, Daniel, 2025, "Code for statesim - a python package to simulate dynamical systems from ordinary differential equations.", https://doi.org/10.18419/DARUS-4769, DaRUS, V1, UNF:6:afs/qXtsE2p0ZWIJY23a/A== [fileUNF]
Python package for simulating ordinary differential equations in state space form. See README.md for details.
Damped pendulum for nonlinear system identification - inputs are sampled from a multivariate-normal distribution - synthetically generated
Feb 26, 2025 - InMotion (EXC)
Frank, Daniel, 2025, "Damped pendulum for nonlinear system identification - inputs are sampled from a multivariate-normal distribution - synthetically generated", https://doi.org/10.18419/DARUS-4770, DaRUS, V1
Overview This dataset contains input-output data of a damped nonlinear pendulum that is actuated at the mounting point. The data was generated with statesim [1], a python package for simulating linear and nonlinear ODEs, for the system actuated pendulum. The configuration .json files for the corresponding datasets (in-distribution and out-of-distri...
Coupled mass-spring-damper system for nonlinear system identification - actuated with random static inputs - synthetically generated
Feb 26, 2025 - InMotion (EXC)
Frank, Daniel, 2025, "Coupled mass-spring-damper system for nonlinear system identification - actuated with random static inputs - synthetically generated", https://doi.org/10.18419/DARUS-4768, DaRUS, V1
Overview This dataset contains input-output data of a coupled mass-spring-damper system with a nonlinear force profile. The data was generated with statesim [1], a python package for simulating linear and nonlinear ODEs, for the system coupled-msd. The configuration .json files for the corresponding datasets (in-distribution and out-of-distribution...
InMotion (EXC)(Universität Stuttgart)
Feb 13, 2025Analytic Computing
Project Website: https://www.ki.uni-stuttgart.de/departments/ac/research/projects/inmotion/
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