Constructing multi-modal emotion recognition model based on convolutional neural network
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
1 Online-Ressource.
- Sprache
-
Englisch
- Erschienen in
-
Constructing multi-modal emotion recognition model based on convolutional neural network ; day:4 ; month:11 ; year:2024 ; pages:1-26
Multimedia tools and applications ; (4.11.2024), 1-26
- Urheber
-
Kuo, Jong-Yih
Hsieh, Ti-Feng
Lin, Ta-Yu
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1007/s11042-024-20409-2
- URN
-
urn:nbn:de:101:1-2501222110387.452000576446
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:28 MESZ
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
- Kuo, Jong-Yih
- Hsieh, Ti-Feng
- Lin, Ta-Yu
- SpringerLink (Online service)
Ähnliche Objekte (12)
WEMAC: Women and Emotion Multi-modal Affective Computing dataset
Multimodal Emotion Recognition Method Based on Convolutional Auto-Encoder
Multi-modal pain intensity recognition based on the SenseEmotion database
Investigation of an efficient multi-modal convolutional neural network for multiple sclerosis lesion detection
Identification of early mild cognitive impairment using multi-modal data and graph convolutional networks
RESIDUAL SHUFFLING CONVOLUTIONAL NEURAL NETWORKS FOR DEEP SEMANTIC IMAGE SEGMENTATION USING MULTI-MODAL DATA
Low-level fusion of audio and video feature for multi-modal emotion recognition
Multichannel Multimodal Emotion Analysis of Cross-Modal Feedback Interactions Based on Knowledge Graph
Multimodal Emotion Recognition
Interactive multi-modal question-answering
Multi-modal Building Energy Management
Multi-modal Battle Royale optimizer
WEMAC: Women and Emotion Multi-modal Affective Computing dataset
Multimodal Emotion Recognition Method Based on Convolutional Auto-Encoder
Multi-modal pain intensity recognition based on the SenseEmotion database
Investigation of an efficient multi-modal convolutional neural network for multiple sclerosis lesion detection
Identification of early mild cognitive impairment using multi-modal data and graph convolutional networks
RESIDUAL SHUFFLING CONVOLUTIONAL NEURAL NETWORKS FOR DEEP SEMANTIC IMAGE SEGMENTATION USING MULTI-MODAL DATA
Low-level fusion of audio and video feature for multi-modal emotion recognition
Multichannel Multimodal Emotion Analysis of Cross-Modal Feedback Interactions Based on Knowledge Graph
Multimodal Emotion Recognition
Interactive multi-modal question-answering
Multi-modal Building Energy Management
Multi-modal Battle Royale optimizer
WEMAC: Women and Emotion Multi-modal Affective Computing dataset
Multimodal Emotion Recognition Method Based on Convolutional Auto-Encoder
Multi-modal pain intensity recognition based on the SenseEmotion database
Investigation of an efficient multi-modal convolutional neural network for multiple sclerosis lesion detection
Identification of early mild cognitive impairment using multi-modal data and graph convolutional networks
RESIDUAL SHUFFLING CONVOLUTIONAL NEURAL NETWORKS FOR DEEP SEMANTIC IMAGE SEGMENTATION USING MULTI-MODAL DATA
Low-level fusion of audio and video feature for multi-modal emotion recognition
Multichannel Multimodal Emotion Analysis of Cross-Modal Feedback Interactions Based on Knowledge Graph
Multimodal Emotion Recognition
Interactive multi-modal question-answering
Multi-modal Building Energy Management