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Nhan đề : 
Meta-transfer learning for emotion recognition
Tác giả : 
Nguyen, Dung
Nguyen, Duc Thanh
Sridha, Sridharan
Năm xuất bản : 
2023
Nhà xuất bản : 
Springer
Tóm tắt : 
Deep learning has been widely adopted in automatic emotion recognition and has lead to significant progress in the field. However, due to insufficient training data, pre-trained models are limited in their generalisation ability, leading to poor performance on novel test sets. To mitigate this challenge, transfer learning performed by fine-tuning pr-etrained models on novel domains has been applied. However, the fine-tuned knowledge may overwrite and/or discard important knowledge learnt in pre-trained models. In this paper, we address this issue by proposing a PathNet-based meta-transfer learning method that is able to (i) transfer emotional knowledge learnt from one visual/audio emotion domain to another domain and (ii) transfer emotional knowledge learnt from multiple audio emotion domains to one another to improve overall emotion recognition accuracy.
Mô tả: 
CC BY
URI: 
https://link.springer.com/article/10.1007/s00521-023-08248-y
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8280
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