EEG emotion recognition based on differential entropy feature matrix through 2D-CNN-LSTM network
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
1 Online-Ressource.
- Sprache
-
Englisch
- Erschienen in
-
EEG emotion recognition based on differential entropy feature matrix through 2D-CNN-LSTM network ; volume:2024 ; number:1 ; day:8 ; month:4 ; year:2024 ; pages:1-19 ; date:12.2024
EURASIP journal on advances in signal processing / European Association for Speech, Signal and Image Processing ; 2024, Heft 1 (8.4.2024), 1-19, 12.2024
- Klassifikation
-
Informatik
- Urheber
-
Wang, Teng
Huang, Xiaoqiao
Xiao, Zenan
Cai, Wude
Tai, Yonghang
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1186/s13634-024-01146-y
- URN
-
urn:nbn:de:101:1-2406241008321.490763925922
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:57 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
- Wang, Teng
- Huang, Xiaoqiao
- Xiao, Zenan
- Cai, Wude
- Tai, Yonghang
- SpringerLink (Online service)
Ähnliche Objekte (12)
A CNN-BiLSTM Deep Learning Model for Automatic Scoring of EEG Signals
Automated recognition of epilepsy from EEG signals using a combining space–time algorithm of CNN-LSTM
EEG-based emotion recognition using multi-scale dynamic CNN and gated transformer
Extracting the Auditory Attention in a Dual-Speaker Scenario From EEG Using a Joint CNN-LSTM Model
Analysis of EEG entropy during visual evocation of emotion in schizophrenia
Electrocardiogram generation with a bidirectional LSTM-CNN generative adversarial network
Air fare sentiment via Backtranslation-CNN-BiLSTM and BERTopic
ECG signal classification based on deep CNN and BiLSTM
EEG based emotion recognition using entropy features and Bayesian optimized random forest
EEG-based human emotion recognition using entropy as a feature extraction measure
Speech emotion classification using atention-based LSTM
No-reference video quality assessment via pretrained CNN and LSTM networks
A CNN-BiLSTM Deep Learning Model for Automatic Scoring of EEG Signals
Automated recognition of epilepsy from EEG signals using a combining space–time algorithm of CNN-LSTM
EEG-based emotion recognition using multi-scale dynamic CNN and gated transformer
Extracting the Auditory Attention in a Dual-Speaker Scenario From EEG Using a Joint CNN-LSTM Model
Analysis of EEG entropy during visual evocation of emotion in schizophrenia
Electrocardiogram generation with a bidirectional LSTM-CNN generative adversarial network
Air fare sentiment via Backtranslation-CNN-BiLSTM and BERTopic
ECG signal classification based on deep CNN and BiLSTM
EEG based emotion recognition using entropy features and Bayesian optimized random forest
EEG-based human emotion recognition using entropy as a feature extraction measure
Speech emotion classification using atention-based LSTM
No-reference video quality assessment via pretrained CNN and LSTM networks
A CNN-BiLSTM Deep Learning Model for Automatic Scoring of EEG Signals
Automated recognition of epilepsy from EEG signals using a combining space–time algorithm of CNN-LSTM
EEG-based emotion recognition using multi-scale dynamic CNN and gated transformer
Extracting the Auditory Attention in a Dual-Speaker Scenario From EEG Using a Joint CNN-LSTM Model
Analysis of EEG entropy during visual evocation of emotion in schizophrenia
Electrocardiogram generation with a bidirectional LSTM-CNN generative adversarial network
Air fare sentiment via Backtranslation-CNN-BiLSTM and BERTopic
ECG signal classification based on deep CNN and BiLSTM
EEG based emotion recognition using entropy features and Bayesian optimized random forest
EEG-based human emotion recognition using entropy as a feature extraction measure
Speech emotion classification using atention-based LSTM