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Proceedings of the Upper-Rhine Artificial Intelligence Symposium 2024
URAI 2024 was hosted by the Institute for Machine Learning and Analytics at Offenburg University on November 13th and 14th. The theme for URAI'24 was "Applied AI in the age of Generative AI".
All submissions received at least two independent reviews from members of the PC in a single blind setting. The papers were accepted for oral or poster presentation.General chairs: Klaus Dorer (HS Offenburg) and Janis Keuper (HS Offenburg)
Program Committee: Klaus Dorer (HS Offenburg), Uwe Haneke (HS Karlsruhe), Janis Keuper (HS Offenburg), Thomas Lampert (Université de Strasbourg), Tobias Lauer (HS Offenburg), Jean-Philippe Lauffenburger (Université de Haute-Alsace), Stefan Naumann (HS Trier), Daniela Oelke (HS Offenburg), Maja Temerinac-Ott (HS Furtwangen), Christoph Reich (HS Furtwangen), Susanne Suter (FH Nordwestschweiz), Dieter Wallach (HS Kaiserslautern)
Website: http://urai24.org
ISBN: 978-3-943301-34-2
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UR-AI2023 : The Upper-Rhine Artificial Intelligence Symposium : Artificial Intelligence for Time Series, Robotics and Beyond
The 5th "Upper Rhine Artificial Intelligence Symposium" (URAI) took place on 17.11.23 at ENSISA in cooperation with IRIMAS (Institut de Recherche en Informatique, Mathématiques, Automatique et Signal) of the Université de Haute-Alsace. It was preceded on 16.11.23 by an autumn school for students of TriRhenaTech partner institutions.
The symposium highlighted current applications of artificial intelligence in cooperation with industrial and scientific partners. The motto of the URAI 2023 event was AI for time series, robotics and beyond.
Topics included, but were not limited to : image and scene understanding, natural language processing, machine learning, data mining, reasoning, efficient computing, deployment and operation of AI systems, architectures for AI, AI in and for education, social and ethical impact, applications of AI in various fields.
Website: https://urai2023.sciencesconf.org/
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UR-AI 2021 : Artificial Intelligence : Application in Life Sciences and Beyond
Collection of Accepted Papers of the Symposium
The TriRhenaTech alliance presents the accepted papers of the 'Upper-Rhine Artificial Intelligence Symposium' held on October 27th 2021 in Kaiserslautern, Germany. Topics of the conference are applications of Artificial Intellgence in life sciences, intelligent systems, industry 4.0, mobility and others. The TriRhenaTech alliance is a network of universities in the Upper-Rhine Trinational Metropolitan Region comprising of the German universities of applied sciences in Furtwangen, Kaiserslautern, Karlsruhe, Offenburg and Trier, the Baden-Wuerttemberg Cooperative State University Loerrach, the French university network Alsace Tech (comprised of 14 'grandes écoles' in the fields of engineering, architecture and management) and the University of Applied Sciences and Arts Northwestern Switzerland. The alliance's common goal is to reinforce the transfer of knowledge, research, and technology, as well as the cross-border mobility of students.
Original publication: https://doi.org/10.48550/arXiv.2112.05657
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UR-AI 2020 : Artificial Intelligence : Research Impact on Key Industries
Collection of Accepted Papers of the canceled Symposium
The TriRhenaTech alliance presents a collection of accepted papers of the cancelled tri-national 'Upper-Rhine Artificial Intelligence Symposium' planned for 13th May 2020 in Karlsruhe. The TriRhenaTech alliance is a network of universities in the Upper-Rhine Trinational Metropolitan Region comprising of the German universities of applied sciences in Furtwangen, Kaiserslautern, Karlsruhe, and Offenburg, the Baden-Wuerttemberg Cooperative State University Loerrach, the French university network Alsace Tech (comprised of 14 'grandes écoles' in the fields of engineering, architecture and management) and the University of Applied Sciences and Arts Northwestern Switzerland. The alliance's common goal is to reinforce the transfer of knowledge, research, and technology, as well as the cross-border mobility of students.
ISBN: 978-3-943301-29-8
Original publication: https://doi.org/10.48550/arXiv.2010.16241