Enhanced Emotion Recognition Using a Hybrid Autoencoder-LSTM Model Optimized with a Hybrid ACO-WOA Algorithm for Hyperparameter Tuning

Emotion recognition is vital in the human Computer interaction because it improves interaction. Therefore, this paper proposes an improved method for emotion recognition regarding the Hybrid Autoencoder-Long Short-Term Memory (LSTM) model and the newly developed hybrid approach of the Ant Colony Opt...

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Veröffentlicht in:	International journal of advanced computer science & applications Jg. 16; H. 4
Hauptverfasser:	Waiker, Vinod, Ramesh, Janjhyam Venkata Naga, Bala, Kiran, Krishnaiah, V. V. Jaya Rama, Jackulin, T., Muniyandy, Elangovan, Shahin, Osama R.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	West Yorkshire Science and Information (SAI) Organization Limited 2025
Schlagworte:	Accuracy Algorithms Ant colony optimization Automation College professors Computer science Datasets Deep learning Emotion recognition Emotions Engineering Machine learning Optimization algorithms Social networks Tuning
ISSN:	2158-107X, 2156-5570
Online-Zugang:	Volltext
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