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Compression of a Deep Competitive Network Based on Mutual Information for Underwater Acoustic Targets Recognition
The accuracy of underwater acoustic targets recognition via limited ship radiated noise can be improved by a deep neural network trained with a large number of unlabeled samples. However, redundant features learned by deep neural network have negative effects on recognition accuracy and efficiency....
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512758/ https://www.ncbi.nlm.nih.gov/pubmed/33265334 http://dx.doi.org/10.3390/e20040243 |