- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource, 1 online resource.
- Language
-
Englisch
- Bibliographic citation
-
Meta-transfer learning for emotion recognition ; volume:35 ; number:14 ; day:24 ; month:1 ; year:2023 ; pages:10535-10549 ; date:5.2023
Neural computing & applications ; 35, Heft 14 (24.1.2023), 10535-10549, 5.2023
- Creator
-
Nguyen, Dung
Nguyen, Duc Thanh
Sridharan, Sridha
Denman, Simon
Nguyen, Thanh Thi
Dean, David
Fookes, Clinton
- Contributor
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SpringerLink (Online service)
- DOI
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10.1007/s00521-023-08248-y
- URN
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urn:nbn:de:101:1-2023090209130358168567
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:59 AM CEST
Data provider
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Associated
- Nguyen, Dung
- Nguyen, Duc Thanh
- Sridharan, Sridha
- Denman, Simon
- Nguyen, Thanh Thi
- Dean, David
- Fookes, Clinton
- SpringerLink (Online service)
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Multi-source transfer learning for facial emotion recognition using multivariate correlation analysis
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Harmonious Mutual Learning for Facial Emotion Recognition
End-to-end modeling and transfer learning for audiovisual emotion recognition in-the-wild
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Feature Transfer Learning for Speech Emotion Recognition
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Sparse autoencoder-based feature transfer learning for speech emotion recognition
Multi-source transfer learning for facial emotion recognition using multivariate correlation analysis
Self-attention transfer networks for speech emotion recognition
Harmonious Mutual Learning for Facial Emotion Recognition
End-to-end modeling and transfer learning for audiovisual emotion recognition in-the-wild
Linked source and target domain subspace feature transfer learning - exemplified by speech emotion recognition
Unsupervised learning in cross-corpus acoustic emotion recognition
Learning with synthesized speech for automatic emotion recognition
Feature Transfer Learning for Speech Emotion Recognition
Personalized models for facial emotion recognition through transfer learning
Transfer Learning in Facial Emotion Recognition: Useful or Misleading?
Deep cross-domain transfer for emotion recognition via joint learning
Sparse autoencoder-based feature transfer learning for speech emotion recognition
Multi-source transfer learning for facial emotion recognition using multivariate correlation analysis
Self-attention transfer networks for speech emotion recognition
Harmonious Mutual Learning for Facial Emotion Recognition
End-to-end modeling and transfer learning for audiovisual emotion recognition in-the-wild
Linked source and target domain subspace feature transfer learning - exemplified by speech emotion recognition
Unsupervised learning in cross-corpus acoustic emotion recognition