| Autor: |
Donia Ammous, Achraf Chabbouh, Awatef Edhib, Ahmed Chaari, Fahmi Kammoun, Nouri Masmoudi |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Journal of Electrical and Computer Engineering, Vol 2023 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2090-0155 |
| DOI: |
10.1155/2023/9351345 |
| Popis: |
Implementing an efficient system for emotion recognition has recently posed a challenge that has not been fully developed yet. Facial emotion recognition (FER) is an important subject matter in the fields of artificial intelligence (AI) since it exhibits a greater commercial potential. This technique is used to analyse various sentiments and reveal a person’s behavior. It could be related to the mental or physiological state of mind. This paper mainly focuses on a human emotion recognition system through a detected human face. Its accuracy was improved via different data augmentation tools, early stopping, and generative adversarial networks (GANs). Compared to previous methods, experimental results show that the proposed method provides a 0.55% to 35.7% gain performance. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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