University of Bahrain
Scientific Journals

Sounds Recognition in the Battlefield Using Convolutional Neural Network

Show simple item record Nahar, Khalid M.O. Al-Omari, Fedaa Alhindawi, Nouh Banikhalaf, Mustafa 2022-02-12T01:20:43Z 2022-02-12T01:20:43Z 2022-02-15
dc.identifier.issn 2210-142X
dc.description.abstract Predicting enemy movements on the battlefield, especially when military raids occur is one of the important factors in battle winning. The enemies may be far away or hidden, but sounds are heard. Based on sounds that are outcomes from hidden enemies and by identifying the type of sound, a lot of information could be gained in further physical processing. The approximate location, distance, and the sound direction could be predicted. Moreover, establishing a sensitive model that relies on distinguishing military sounds will assist soldiers in alerting their military troops or camps for a near or faraway danger. Therefore, in this research, we build a Convolutional Neural Network (CNN) model for sound recognition in the battlefield. The mel frequency cepstral coefficients (MFCCs) features is used in this research to distinguish five types of sound; soldiers marching sound, plane sound, refiles sound, military vehicle sound, and missile launchers sound. The results showed that the CNN model accomplished the mission with an accuracy of 95.3% on testing data, while it showed 93.6% of accuracy on the outlet or unseen data. As a novel attempt and idea, the results were so promising. en_US
dc.language.iso en en_US
dc.publisher University Of Bahrain en_US
dc.subject Convolutional Neural Network (CNN) en_US
dc.subject Deep Learning en_US
dc.subject Sounds Recognition en_US
dc.subject MFCC en_US
dc.subject Sound Classification en_US
dc.subject Battlefield Sounds en_US
dc.title Sounds Recognition in the Battlefield Using Convolutional Neural Network en_US
dc.volume 11 en_US
dc.issue 1 en_US
dc.pagestart 189 en_US
dc.pageend 198 en_US
dc.contributor.authorcountry Jordan en_US
dc.contributor.authoraffiliation Department of Computer Sciences, Yarmouk University en_US
dc.contributor.authoraffiliation Directorate of Education of the District of Qasbah Irbid, Irbid Governorate en_US
dc.contributor.authoraffiliation Department of Computer Science and Software Engineering, Faculty of Sciences and Information Technology, Jadara University en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US

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