Sonar Image Target Detection and Recognition Based on Convolution Neural Network

Recent advancements in deep learning offer an effective approach for the study in machine vision using optical images. In this paper, a convolution neural network is used to deal with the target task of sonar detection, and the performance of each neural network model in the sonar image detection an...

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Bibliographic Details
Published inMobile information systems Vol. 2021; pp. 1 - 8
Main Author Yanchen, Wu
Format Journal Article
LanguageEnglish
Published Amsterdam Hindawi 22.03.2021
Hindawi Limited
Subjects
Algorithms
Artificial neural networks
Classification
Convolution
Deep learning
Image detection
Machine learning
Machine vision
Model accuracy
Neural networks
Object recognition
Regions
Remote sensing
Semantics
Sonar
Target detection
Target recognition
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Summary:Recent advancements in deep learning offer an effective approach for the study in machine vision using optical images. In this paper, a convolution neural network is used to deal with the target task of sonar detection, and the performance of each neural network model in the sonar image detection and recognition task of underwater box and tire is compared. The simulation results show that the neural network method proposed in this paper is better than the traditional machine learning methods and SSD network models. The average accuracy of the proposed method for sonar image target recognition is 93%, and the detection time of a single image is only 0.3 seconds.
ISSN:1574-017X
1875-905X
DOI:10.1155/2021/5589154