Publisher
Springer Science and Business Media LLC
Subject
Earth and Planetary Sciences (miscellaneous),Geography, Planning and Development
Reference58 articles.
1. Abdollahi, A., Pradhan, B., Shukla, N., Chakraborty, S., & Alamri, A. (2020). Deep learning approaches applied to remote sensing datasets for road extraction: A state-of-the-art review. Remote Sensing. https://doi.org/10.3390/rs12091444
2. Alshaikhli, T., Liu, W., & Maruyama, Y. (2019). Automated method of road extraction from aerial images using a deep convolutional neural network. Applied Sciences. https://doi.org/10.3390/app9224825
3. Alshehhi, R., Marpu, P. R., Woon, W. L., & Mura, M. D. (2017). Simultaneous extraction of roads and buildings in remote sensing imagery with convolutional neural networks. ISPRS Journal of Photogrammetry and Remote Sensing, 130, 139–149. https://doi.org/10.1016/j.isprsjprs.2017.05.002
4. Bacher, U., & Mayer, H. (2012). Automatic road extraction from multispectral high resolution satellite images. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36.
5. Badrinarayanan, V., Kendall, A., & Cipolla, R. (2017). SegNet: A deep convolutional encoder-decoder architecture for image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(12), 2481–2495. https://doi.org/10.1109/TPAMI.2016.2644615
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