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- Dokumenttyp:
- Konferenzbeitrag
- Autor(en):
- Maier, Marco; Elsner, Daniel; Marouane, Chadly; Zehnle, Meike; Fuchs, Christoph
- Nicht-TUM Koautoren:
- ja
- Kooperation:
- national
- Titel:
- DeepFlow: Detecting Optimal User Experience From Physiological Data Using Deep Neural Networks
- Intellectual Contribution:
- Discipline-based Research
- Kongress- / Buchtitel:
- Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence
- Kongress / Zusatzinformationen:
- Macau, China
- Verlag / Institution:
- International Joint Conferences on Artificial Intelligence Organization
- Publikationsdatum:
- 01.08.2019
- Jahr:
- 2019
- Monat:
- Jul
- Print-ISBN:
- 9780999241141
- Volltext / DOI:
- doi:10.24963/ijcai.2019/196
- Key publication:
- Nein
- Peer reviewed:
- Ja
- International:
- Ja
- Book review:
- Nein
- commissioned:
- not commissioned
- Interdisziplinarität:
- Ja
- Leitbild:
- Energy, Climate, Environment
- Technology:
- Ja
- Ethics und Sustainability:
- Nein
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