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Authors: Md Atiqur Rahman and Abdelhamid Mammeri

Affiliation: National Research Council Canada, Ottawa, Canada

Keyword(s): Vegetation Detection on Railway Tracks, Drone-based Vegetation Detection, Image Semantic Segmentation.

Abstract: Vegetation management on and alongside the railway tracks is very crucial for safe railway operations. The railway industry, therefore, needs to regularly monitor the growth of vegetation on railway tracks and embankments and mostly relies on human inspectors for the inspection and monitoring. This manual process being prohibitively time-consuming and cost-ineffective, there is a growing need to automate the process of vegetation detection. Aerial imagery collected using Unmanned Aerial Vehicles (UAVs) is becoming increasingly popular for automated inspection and monitoring. On the other hand, due to their recent success, Deep Convolutional Neural Networks (DCNNs) have seen rapid deployment in a wide array of image understanding tasks. In this work, we therefore, investigate the effectiveness of DCNNs for automating the vegetation detection task using UAV imagery. We further propose simple yet effective modification to an existing DCNN architecture and demonstrate its efficacy for ve getation detection using publicly available dataset. (More)

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Paper citation in several formats:
Rahman, M. and Mammeri, A. (2021). Vegetation Detection in UAV Imagery for Railway Monitoring. In Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS; ISBN 978-989-758-513-5; ISSN 2184-495X, SciTePress, pages 457-464. DOI: 10.5220/0010439904570464

@conference{vehits21,
author={Md Atiqur Rahman. and Abdelhamid Mammeri.},
title={Vegetation Detection in UAV Imagery for Railway Monitoring},
booktitle={Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS},
year={2021},
pages={457-464},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010439904570464},
isbn={978-989-758-513-5},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS
TI - Vegetation Detection in UAV Imagery for Railway Monitoring
SN - 978-989-758-513-5
IS - 2184-495X
AU - Rahman, M.
AU - Mammeri, A.
PY - 2021
SP - 457
EP - 464
DO - 10.5220/0010439904570464
PB - SciTePress

- Science and Technology Publications, Lda.
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