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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....
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| Pubblicato in: | Entropy (Basel) |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI
2018
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7512758/ https://ncbi.nlm.nih.gov/pubmed/33265334 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e20040243 |
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