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A comprehensive review on landmine detection using deep learning techniques in 5G environment: open issues and challenges

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Abstract

Detection of Landmines, especially anti-tank mines, bombs, and unexploded substances, is one of the major challenges facing humanity. The devastation and human tragedy associated with undetected explosives are self-evident in war-torn communities. To deal with this problem, we are only left with proactive measures that such substances must be detected and dealt with before the fallout. Most available solutions have major shortcomings, such as cost, efficiency, and accuracy, where the trade-offs among them are inversely related. On the other hand, advances in deep learning, unmanned aerial vehicle, and sensing are making their way as potential technologies to revolutionize the detection and removal of landmines. In this paper, we go through the literature reviewing the most recent work featuring computerized technologies to detect landmines. To our knowledge, no such study has taken place in this respect. Our aim is to find out how deep learning can be integrated with landmine detection. We identify open challenges toward viable automated solutions that enable deep learning to optimize performance effectively.

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Acknowledgements

This research work was funded by Institutional Fund Projects under grant no (IFPNC-001-611-2020). Therefore, the authors gratefully acknowledge technical and financial support from the Ministry of Education and King Abdelaziz University, Jeddah, Saudi Arabia.

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Authors and Affiliations

  1. Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia

    Ahmed Barnawi, Bander Alzahrani, Amal Almansour & Adeeb Noor

  2. School of Computer Science Engineering and Technology, Greater Noida, Uttar Pradesh, India

    Ishan Budhiraja

  3. Thapar Institute of Engineering and Technology, Patiala, Punjab, India

    Krishan Kumar & Neeraj Kumar

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  1. Ahmed Barnawi
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Barnawi, A., Budhiraja, I., Kumar, K. et al. A comprehensive review on landmine detection using deep learning techniques in 5G environment: open issues and challenges. Neural Comput & Applic 34, 21657–21676 (2022). https://doi.org/10.1007/s00521-022-07819-9

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