Few-shot learning for joint model in underwater acoustic target recognition

In underwater acoustic target recognition, there is a lack of massive high-quality labeled samples to train robust deep neural networks, and it is difficult to collect and annotate a large amount of base class data in advance unlike the image recognition field. Therefore, conventional few-shot learn...

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Detalles Bibliográficos
Autores principales: Tian, Shengzhao, Bai, Di, Zhou, Junlin, Fu, Yan, Chen, Duanbing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10579255/
https://www.ncbi.nlm.nih.gov/pubmed/37845288
http://dx.doi.org/10.1038/s41598-023-44641-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10579255/
https://www.ncbi.nlm.nih.gov/pubmed/37845288
http://dx.doi.org/10.1038/s41598-023-44641-2

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