UAV Image-based Automated Road Damage Detection using Deep Learning

Authors

  • B. Sunitha, Veggalam Sai Nagarjuna, Chenna Janaki, Dugyala Likitha, Boddu Prudhviraj

Keywords:

Keywords: UAV, Road damage detection, Deep learning, Convolutional Neural Networks (CNNs), Automated inspection

Abstract

In recent years, the rapid advancement of Unmanned Aerial Vehicles (UAVs) has paved the way forinnovative applications across various sectors. One such promising application is the automateddetection of road damage, a critical task for maintaining road infrastructure and ensuringtransportation safety. Traditional road damage detection systems predominantly rely on manualinspections or vehicle-mounted cameras, which are often time-consuming

References

H. S. S. Blas, A. C. Balea, A. S. Mendes, L. A. Silva, and G. V. González, “A platform for swimming pool detection and legal verification using a multi-agent system and remote image sensing,” International Journal of Interactive Multimedia and Artificial Intelligence, vol. In Press, no. In Press, pp. 1–13, 2023.

V. J. Hodge, R. Hawkins, and R. Alexander, “Deep reinforcement learning for drone navigation using sensor data,” Neural Computing and Applications, vol. 33, no. 6, pp. 2015–2033, Jun. 2020

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Published

2025-04-21

How to Cite

B. Sunitha, Veggalam Sai Nagarjuna, Chenna Janaki, Dugyala Likitha, Boddu Prudhviraj. (2025). UAV Image-based Automated Road Damage Detection using Deep Learning. Journal of Computational Analysis and Applications (JoCAAA), 34(4), 440–452. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2316

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Articles

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