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doans / Underwater-Acoustic-Target-Classification-Based-on-Dense-Convolutional-Neural-Network

In oceanic remote sensing operations, underwater acoustic target recognition is always a difficult and extremely important task of sonar systems, especially in the condition of complex sound wave propagation characteristics. Expensively learning recognition model for big data analysis is typically an obstacle for most traditional machine learning (ML) algorithms, whereas convolutional neural network (CNN), a type of deep neural network, can automatically extract features for accurate classification. In this study, we propose an approach using a dense CNN model for underwater target recognition. The network architecture is designed to cleverly re-use all former feature maps to optimize classification rate under various impaired conditions while satisfying low computational cost. In addition, instead of using time-frequency spectrogram images, the proposed scheme allows directly utilizing original audio signal in time domain as the network input data. Based on the experimental results evaluated on the real-world dataset of passive sonar, our classification model achieves the overall accuracy of 98.85$\%$ at 0 dB signal-to-noise ratio (SNR) and outperforms traditional ML techniques, as well as other state-of-the-art CNN models.

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Hello, Thank you for considering my dataset. I download it normally. You can download with this link: https://mega.nz/folder/q1tgjJCA#GO8yhqz0s5Jm1pf18Vz9qA Best regards, Ing. Doan Van Sang, Ph.D. Faculty of Communication and Radar Vietnam Naval Academy

On Sat, Dec 25, 2021 at 1:32 PM mayanxin89 @.***> wrote:

Can you provide other open ways to download the dataset? I cannot log in to the SharePoint official website. Thank you very much!

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Hi, Due to management policy for the dataset, I don't have permission to share with you the exact names of those classes. That's reason why we marked the classes as Noi T01 to T11. Hope you understand this issue. Thank you and best regards, Sang

On Thu, Feb 1, 2024, 10:03 PM Momin @.***> wrote:

Thanks for sharing the dataset! I had one question regarding it. What do different class labels refer to?

I see the class folders as: class_folders = ['Noi', 'T01', 'T02', 'T03', 'T04', 'T05', 'T06', 'T07', 'T08', 'T09', 'T10', 'T11'] But what do these classes represent? What is T1, T2......T11? As in is T1="Passenger Ships", T2="Tanker Ship" etc?

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doans / Underwater-Acoustic-Target-Classification-Based-on-Dense-Convolutional-Neural-Network

Dateset help #2

What do different class labels refer to?