Interpretation of human emotions through multimodal data: a dual-encoder transformer approach
Conti, Silvia (A.A. 2023/2024) Interpretation of human emotions through multimodal data: a dual-encoder transformer approach. Tesi di Laurea in Machine learning, Luiss Guido Carli, relatore Giuseppe Francesco Italiano, pp. 54. [Master's Degree Thesis]
Full text for this thesis not available from the repository.
Abstract/Index
Sentiment analysis. Levels of sentiment analysis. Techniques of sentiment analysis. Aspect based sentiment analysis. Multimodal aspect-based sentiment analysis. Multimodal aspect sentiment classification methods. Aspect sentiment pairs extraction methods. MABSA datasets. Dual-encoder transformers with cross modal alignment. Dual-encoder transformer architecture. Techniques for cross modal alignment.
References
Bibliografia: pp. 51-53.
Thesis Type: | Master's Degree Thesis |
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Institution: | Luiss Guido Carli |
Degree Program: | Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91) |
Chair: | Machine learning |
Thesis Supervisor: | Italiano, Giuseppe Francesco |
Thesis Co-Supervisor: | Simeone, Antonio |
Academic Year: | 2023/2024 |
Session: | Autumn |
Deposited by: | Alessandro Perfetti |
Date Deposited: | 09 Jun 2025 09:46 |
Last Modified: | 09 Jun 2025 09:46 |
URI: | https://tesi.luiss.it/id/eprint/42343 |
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