Machine Learning Ship Classifiers for Signals from Passive Sonars
The accurate automatic classification of underwater acoustic signals from passive SoNaR is vital for naval operational readiness, enabling timely vessel identification and real-time maritime surveillance. This study evaluated seven supervised machine learning algorithms for ship identification using...
Saved in:
Main Authors: | Allyson A. da Silva, Lisandro Lovisolo, Tadeu N. Ferreira |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-06-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/15/13/6952 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Passive sonar with cylindrical array
by: J. Marszal, et al.
Published: (2014-01-01) -
Detection Range of Intercept Sonar for CWFM Signals
by: Jacek MARSZAL, et al.
Published: (2014-06-01) -
Noise immunity increase of sonar signals from the complex bodies identification and recognition against reverberation interferences
by: V. S. Davidov
Published: (2015-04-01) -
Visualisation forms in passive sonar with towed array
by: A. Raganowicz, et al.
Published: (2014-01-01) -
Experimental Study of Silent Sonar
by: Jacek MARSZAL
Published: (2014-03-01)