Underwater Acoustic Classification
1 papers with code • 0 benchmarks • 0 datasets
Classification of underwater acoustic data
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Most implemented papers
An Investigation of Preprocessing Filters and Deep Learning Methods for Vessel Type Classification With Underwater Acoustic Data
However, high accuracies of 94. 95% were achieved using CQT as the preprocessing filter for a ResNet-based convolutional neural network, providing a trade-off between model complexity and accuracy; a result that is more than 10% higher than previously reported approaches.