Dr. Mingda Liu Profile

Dr. Mingda Liu

at Institute of Acoustics

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 27 March 2022 Paper

Feature visualizations in geoacoustic inversion using convolutional neural network

Mingda Liu, Haiqiang Niu, Zhenglin Li

Proceedings Volume 12169, 1216960 (2022) https://doi.org/10.1117/12.2624657

KEYWORDS: Visualization, Feature extraction, Convolution, Acoustics, Data modeling, Convolutional neural networks

Read Abstract +

The acoustic signals propagating in different environments have distinct features which are related to the geoacoustic parameters. A convolutional neural network (CNN) is applied to extract features from signals in the frequency domain to estimate the geoacoustic parameters in shallow water. The outputs of the trained CNN layers with different depths are visualized to express the features extracted from the input data. The network input is the normalized sample covariance matrices (SCMs) of the broadband data received by a vertical line array. Simulated acoustic data generated by the acoustic propagation model are used as the training data, validation data, and test data. Simulation visualization results demonstrate that the trained CNN can extract features of geoacoustic parameters and have good robustness in geoacoustic inversion even on noisy test data.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years