Performance analysis of rule-based classification and deep learning method for automatic road extraction

Author:

BAYRAMOĞLU Zeynep,UZAR Melis

Publisher

International Journal of Engineering and Geoscience

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference34 articles.

1. Fetai B, Ostir K, Kosmatin Fras M & Lisec A (2019). Extraction of visible boundaries for cadastral mapping based on UAV ımagery. Remote Sensing, 11(13), 2-20.

2. Kavzoğlu T & Tombul H (2017). Nesne Tabanlı Sınıflandırmada Segmentasyon Kalitesinin Sınıflandırma Doğruluğu Üzerine Etkisinin İncelenmesi. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 17(1), 118-125.

3. 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, 12(9), 4-22.

4. Lian R, Wang W, Mustafa N & Huang L (2020). Road Extraction Methods in High-Resolution Remote Sensing Images: A Comprehensive Review. IEEE journal of selected topics in applıed earth observations and remote sensing, 11(5), 552, 2-16.

5. Yadav DP, Nagarajan K, Pande H, Tiwari P, Narawade R (2020). Automatic urban road extraction from high resolution satellite data using object based ımage analysis: a fuzzy classification approach. Journal of Remote Sensing & GIS, 9(1), 279, 1-8.

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