Rail Tracking and Detection with Drone in Gazebo Environment
Author:
Publisher
European Journal of Science and Technology
Subject
General Earth and Planetary Sciences,General Environmental Science
Reference18 articles.
1. Aydın, I., Akin, E., & Karakose, M. (2021). Defect classification based on deep features for railway tracks in sustainable transportation. Applied Soft Computing, 111, 107706. https://doi.org/10.1016/j.asoc.2021.107706.
2. Singhal, V., Anand, D., Aljahdali, H. M., Goyal, N., Singh, A., & Kadry, S. (2021). An Intelligent and Autonomous Sight Distance Evaluation Framework for Sustainable Transportation. Sustainability, 13(16), 8885. https://doi.org/10.3390/su13168885.
3. Rahman, M. A., & Mammeri, A. (2021). Vegetation Detection in UAV Imagery for Railway Monitoring. Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems. https://doi.org/10.5220/0010439904570464.
4. Máthé, K., & Buşoniu, L. (2015). Vision and Control for UAVs: A Survey of General Methods and of Inexpensive Platforms for Infrastructure Inspection. Sensors, 15(7), 14887–14916. https://doi.org/10.3390/s150714887.
5. Páli, E., Máthé, K., Tamás, L., & Buşoniu, L. (2014). Railway track following with the AR.Drone using vanishing point detection. IEEE Xplore. https://doi.org/10.1109/AQTR.2014.6857870.
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