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Dr.-Ing. Jan Alexandersson

Organizational unit Cognitive Assistants
Contact +49 681 85775 5347 (Saarbrücken)

http://www.dfki.de/~janal/
Address (Saarbrücken) Gebäude D3 1Stuhlsatzenhausweg 3D-66123 Saarbrücken

Publications

M3TCM: Multi-modal Multi-task Context Model for Utterance Classification in Motivational Interviews

Sayed Muddashir Hossain; Jan Alexandersson; Philipp Müller

In: Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation. Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING-2024), ACL, 2024.

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MultiMediate'24: Multi-Domain Engagement Estimation

Philipp Müller; Michal Balazia; Tobias Baur; Michael Dietz; Alexander Heimerl; Anna Penzkofer; Dominik Schiller; François Brémond; Jan Alexandersson; Elisabeth André; Andreas Bulling

In: Proceedings of the 32nd ACM International Conference on Multimedia. ACM International Conference on Multimedia (ACM MM-2024), New York, NY, USA, MM '24, ISBN 9798400706868, Association for Computing Machinery, 2024.

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Recognizing Emotion Regulation Strategies from Human Behavior with Large Language Models

Philipp Müller; Alexander Heimerl; Sayed Muddashir Hossain; Lea Siegel; Jan Alexandersson; Patrick Gebhard; Elisabeth André; Tanja Schneeberger

In: 2024 12th International Conference on Affective Computing and Intelligent Interaction (ACII). International Conference on Affective Computation and Intelligent Interaction (ACII-2024), September 15-18, Glasgow, United Kingdom, IEEE, 2024.

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All publications

Profile

  • GAIN

    Georgian Artificial Intelligence Networking and Twinning Initiative

  • KI@Home

    Prädiktion von adverse events mittels Künstlicher Intelligenz und Ambient Assisted Living-Systemen in der Häuslichkeit von pflegebedürftigen Personen

    The goal is to develop a risk assessment module for a smart home platform with a focus on "smart ageing". A collection of sensors is installed in the volunteers' flats and their base health status…

    KI@Home

  • KItatta

    KI-Verfahren erkennen Qualität von Spenderhornhäuten

    In Deutschland werden jährlich mehr als 9.000 Hornhauttransplantationen durchgeführt. Trotz strenger Qualitätskriterien sind bei etwa 4-5 % der Transplantate postoperativ warzenförmige Veränderungen…

    KItatta

  • MePheSTO

    Digital Phenotyping 4 Psychiatric Disorders from Social Interaction

    MePheSTO is an interdisciplinary research project that aims to develop a scientifically grounded, artificial intelligence based methodology for identifying and classifying measurable, and thus…

    MePheSTO

  • AI-Watch

    AI-supported telemonitoring of cardiac condition

    High-risk cardio patients need permanent monitoring, making a normal life difficult or impossible. AIWatch allows them to leave the hospital and live independently, yet safely, with a unique…

    AI-Watch
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