Generative Adversarial Network for Facial Emotion Recognition: A Feasibility Study
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Notes
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In: The Upper-Rhine Artificial Intelligence Symposium UR-AI 2022 : AI Applications in Medicine and Manufacturing, 19 October 2022, Villingen-Schwenningen, Germany. - Furtwangen : Furtwangen University, 2022, S. 132-136. - ISBN 978-3-00-073637-7
- Event
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Veröffentlichung
- (where)
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Furtwangen
- (who)
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Hochschule Furtwangen
- (when)
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2022
- Creator
- URN
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urn:nbn:de:bsz:fn1-opus4-86252
- Rights
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Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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25.03.2025, 1:46 PM CET
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Arabian, Herag
- Möller, Knut
- Hochschule Furtwangen
Time of origin
- 2022
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Global Inhomogeneity Index Evaluation of a DCT-based EIT Lung Imaging
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Traditional versus Neural Network Classification Methods for Facial Emotion Recognition
Emotion Recognition beyond Pixels : Leveraging Facial Point Landmark Meshes
Fourier Series Model for Facial Feature Point Land-Marking
Generative Adversarial Privacy
Image Pre-processing Significance on Regions of Impact in a Trained Network for Facial Emotion Recognition
Global Inhomogeneity Index Evaluation of a DCT-based EIT Lung Imaging
Comparison of a histology based multi layer artery model to its simplified axisymmetric model
Dynamic emotion recognition using histogram of oriented gradients
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