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Schreiber, Andreas und Bock, Marcel (2019) Visualization and Exploration of Deep Learning Networks in 3D and Virtual Reality. In: 21st International Conference on Human-Computer Interaction, HCI International 2019, 1033. Springer, Cham. HCI International 2019, 2019-07-26 - 2019-07-31, Orlando, FL, USA. doi: 10.1007/978-3-030-23528-4_29. ISBN 978-3-030-23527-7.
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Offizielle URL: https://link.springer.com/chapter/10.1007/978-3-030-23528-4_29
Kurzfassung
Understanding of artificial intelligence (AI) systems becomes more important as their use cases in real-world applications growth. Today’s AI systems are increasingly complex and ubiquitous. They will be responsible for making decisions that directly affect individuals. Explainable AI can potentially help by explaining actions, decisions and behaviours of AI systems to users. Our approach is to provide a tool with an interactive user interface in 3D. The tool visualizes deep learning network layers and allows interactive exploration on different levels of detail. The visualization then improves transparency and opacity of AI systems for experts and non-experts.
| elib-URL des Eintrags: | https://elib.dlr.de/128477/ | ||||||||||||
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| Dokumentart: | Konferenzbeitrag (Poster) | ||||||||||||
| Titel: | Visualization and Exploration of Deep Learning Networks in 3D and Virtual Reality | ||||||||||||
| Autoren: |
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| Datum: | 6 Juli 2019 | ||||||||||||
| Erschienen in: | 21st International Conference on Human-Computer Interaction, HCI International 2019 | ||||||||||||
| Referierte Publikation: | Ja | ||||||||||||
| Open Access: | Nein | ||||||||||||
| Gold Open Access: | Nein | ||||||||||||
| In SCOPUS: | Ja | ||||||||||||
| In ISI Web of Science: | Nein | ||||||||||||
| Band: | 1033 | ||||||||||||
| DOI: | 10.1007/978-3-030-23528-4_29 | ||||||||||||
| Herausgeber: |
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| Verlag: | Springer, Cham | ||||||||||||
| Name der Reihe: | Communications in Computer and Information Science | ||||||||||||
| ISBN: | 978-3-030-23527-7 | ||||||||||||
| Status: | veröffentlicht | ||||||||||||
| Stichwörter: | explainable artificial intelligence, deep learning, interpretable machine learning, interactive exploration, visualization | ||||||||||||
| Veranstaltungstitel: | HCI International 2019 | ||||||||||||
| Veranstaltungsort: | Orlando, FL, USA | ||||||||||||
| Veranstaltungsart: | internationale Konferenz | ||||||||||||
| Veranstaltungsbeginn: | 26 Juli 2019 | ||||||||||||
| Veranstaltungsende: | 31 Juli 2019 | ||||||||||||
| HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||
| HGF - Programm: | Raumfahrt | ||||||||||||
| HGF - Programmthema: | Technik für Raumfahrtsysteme | ||||||||||||
| DLR - Schwerpunkt: | Raumfahrt | ||||||||||||
| DLR - Forschungsgebiet: | R SY - Technik für Raumfahrtsysteme | ||||||||||||
| DLR - Teilgebiet (Projekt, Vorhaben): | R - Vorhaben SISTEC (alt) | ||||||||||||
| Standort: | Köln-Porz | ||||||||||||
| Institute & Einrichtungen: | Institut für Simulations- und Softwaretechnik > Verteilte Systeme und Komponentensoftware Institut für Simulations- und Softwaretechnik | ||||||||||||
| Hinterlegt von: | Schreiber, Andreas | ||||||||||||
| Hinterlegt am: | 23 Jul 2019 10:05 | ||||||||||||
| Letzte Änderung: | 24 Apr 2024 20:32 |
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