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All Journal International Journal of Informatics, Information System and Computer Engineering (INJIISCOM)
Md Shahazul Islam
Information and Communication Engineering, Nanjing University of Information Science and Technology, China
Computer Science & IT Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Deep Learning-Based Sonar Image Object Detection System Md Shahazul Islam
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 6 No. 2 (2025): INJIISCOM: VOLUME 6, ISSUE 2, DECEMBER 2025
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v6i2.14431

Abstract

Sonar image object detection is crucial for underwater tasks, yet practical applications of advanced deep learning in this field remain underexplored due to environmental challenges. To bridge this gap, this study proposes a modular, deep learning-based sonar image object detection system. The system comprises three interdependent subsystems: dataset generation, algorithm model training and testing, and model deployment. Designed for high accuracy, speed, portability, and deployment adaptability, it effectively processes challenging sonar data. Experimental results from underwater suspicious object detection tasks confirm that the system achieves reliable, accurate performance and excellent real-world application outcomes. This work significantly advances sonar-based target localization and exploration.
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