Unraveling ML models of emotion with NOVA: multi-level explainable AI for non-experts
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
In: IEEE Transactions on Affective Computing, 13, 3, S. 1155-1167
- Ereignis
-
Veröffentlichung
- (wo)
-
Augsburg
- (wer)
-
Universität Augsburg
- (wann)
-
2022
- Ereignis
-
Veröffentlichung
- (wo)
-
Piscataway, NJ
- (wer)
-
Institute of Electrical and Electronics Engineers (IEEE)
- (wann)
-
2022
- Urheber
- DOI
-
10.1109/taffc.2020.3043603
- URN
-
urn:nbn:de:bvb:384-opus4-832985
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Heimerl, Alexander
- Weitz, Katharina
- Baur, Tobias
- André, Elisabeth
- Universität Augsburg
- Institute of Electrical and Electronics Engineers (IEEE)
Entstanden
- 2022
Ähnliche Objekte (12)
Explainable ML
Using explainable AI to identify differences between clinical and experimental pain detection models based on facial expressions
NOVA - a tool for eXplainable Cooperative Machine Learning
eXplainable cooperative machine learning with NOVA
"Let me explain!": exploring the potential of virtual agents in explainable AI interaction design
Safira - supporting affective interactions in real-time applications
Should we (dis)trust robots? Developing responsible AI using cognitive and affective human-robot trust
Deciding when to react to incremental user input in human-robot interaction
Perception and interactive technologies : proceedings
Abschlussbericht des Bayerischen Forschungsverbunds: gesunder Umgang mit digitalen Technologien und Medien (ForDigitHealth), Juni 2019 – Mai 2023
I see what you did there: understanding when to trust a ML model with NOVA
Relevance-based feature masking: improving neural network based whale classification through explainable artificial intelligence
Explainable ML
Using explainable AI to identify differences between clinical and experimental pain detection models based on facial expressions
NOVA - a tool for eXplainable Cooperative Machine Learning
eXplainable cooperative machine learning with NOVA
"Let me explain!": exploring the potential of virtual agents in explainable AI interaction design
Safira - supporting affective interactions in real-time applications
Should we (dis)trust robots? Developing responsible AI using cognitive and affective human-robot trust
Deciding when to react to incremental user input in human-robot interaction
Perception and interactive technologies : proceedings
Abschlussbericht des Bayerischen Forschungsverbunds: gesunder Umgang mit digitalen Technologien und Medien (ForDigitHealth), Juni 2019 – Mai 2023
I see what you did there: understanding when to trust a ML model with NOVA
Relevance-based feature masking: improving neural network based whale classification through explainable artificial intelligence
Explainable ML
Using explainable AI to identify differences between clinical and experimental pain detection models based on facial expressions
NOVA - a tool for eXplainable Cooperative Machine Learning
eXplainable cooperative machine learning with NOVA
"Let me explain!": exploring the potential of virtual agents in explainable AI interaction design
Safira - supporting affective interactions in real-time applications
Should we (dis)trust robots? Developing responsible AI using cognitive and affective human-robot trust
Deciding when to react to incremental user input in human-robot interaction
Perception and interactive technologies : proceedings
Abschlussbericht des Bayerischen Forschungsverbunds: gesunder Umgang mit digitalen Technologien und Medien (ForDigitHealth), Juni 2019 – Mai 2023
I see what you did there: understanding when to trust a ML model with NOVA