Complex active sonar targets recognition using variable length deep convolutional neural network evolved by biogeography-based optimizer-Reference-Cited by-同舟云学术

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Complex active sonar targets recognition using variable length deep convolutional neural network evolved by biogeography-based optimizer

Published:2022-12-29 Issue: Volume: Page:1-25
ISSN:1745-5030
Container-title:Waves in Random and Complex Media
language:en
Short-container-title:Waves in Random and Complex Media

Author:

Khishe Mohammad¹^ORCID,Mohammadi Mokhtar²,Mohammed Adil Hussein³

Affiliation:

1. Department of Electrical Engineering, Imam Khomeini Marine Science University, Nowshahr, Iran

2. Department of Information Technology, College of Engineering and Computer Science, Lebanese French University, Kurdistan Region, Iraq

3. Department of Communication and Computer Engineering, Faculty of Engineering, Cihan University-Erbil, Kurdistan Region, Iraq

Publisher

Informa UK Limited

Subject

General Physics and Astronomy,General Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/17455030.2022.2155319

Reference88 articles.

1. Overview of Underwater Transmission Characteristics of Oceanic LiDAR

2. Nonlinear Lamb Wave for Structural Incipient Defect Detection with Sequential Probabilistic Ratio Test

3. Radionuclide transport in multi-scale fractured rocks: A review

4. Capacity of communication link with carrier of vortex localized wave in absorptive turbulent seawater

5. Multi-Sensor Fusion by CWT-PARAFAC-IPSO-SVM for Intelligent Mechanical Fault Diagnosis

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2. An improved dung beetle optimization with recurrent convolutional neural networks for efficient detection and classification of undersea water object images;Earth Science Informatics;2024-06-18

3. MSLEFC: A low-frequency focused underwater acoustic signal classification and analysis system;Engineering Applications of Artificial Intelligence;2023-08

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