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Auditory Inspired Convolutional Neural Networks for Ship Type Classification with Raw Hydrophone Data
Detecting and classifying ships based on radiated noise provide practical guidelines for the reduction of underwater noise footprint of shipping. In this paper, the detection and classification are implemented by auditory inspired convolutional neural networks trained from raw underwater acoustic si...
में बचाया:
| में प्रकाशित: | Entropy (Basel) |
|---|---|
| मुख्य लेखकों: | , , , , |
| स्वरूप: | Artigo |
| भाषा: | Inglês |
| प्रकाशित: |
MDPI
2018
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| विषय: | |
| ऑनलाइन पहुंच: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7512589/ https://ncbi.nlm.nih.gov/pubmed/33266713 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e20120990 |
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