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Real Time Object Detection for Autonomous AUVS Using an Attention–Based Fast–Rcnn Framework Cover

Real Time Object Detection for Autonomous AUVS Using an Attention–Based Fast–Rcnn Framework

International Journal of Applied Mathematics and Computer Science
Volume 36 (2026): Issue 1 (March 2026)
By: Mohcine Boudhane and  Hamza Toulni  
Open Access
|Mar 2026

Authors

Mohcine Boudhane

m.boudhane@uiz.ac.ma

LabSI & National School of Artificial Intelligence and Data Science Taroudant Ibn Zohr University, Agadir, Morocco
Socio-Technical Systems Engineering, Institute Vidzeme University of Applied Sciences, Valmiera, Latvia

Hamza Toulni

Department of Computer Science, Rabat National School of Mines (ENSMR) Hadj Ahmed Cherkaoui Avenue, Rabat, Morocco
DOI: https://doi.org/10.61822/amcs-2026-0006 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
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Language: English
Page range: 67 - 79
Submitted on: Aug 19, 2025
|
Accepted on: Nov 21, 2025
|
Published on: Mar 21, 2026
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
underwater monitoring,
deep learning,
object detection and identification,
AUVs,
optical images,
underwater robotics,
intelligent robots
Related subjects:
Mathematics,
Applied mathematics

© 2026 Mohcine Boudhane, Hamza Toulni, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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