Author:
Rostami Omid,Kaveh Mehrdad
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,Computational Theory and Mathematics,Computers in Earth Sciences,Computer Science Applications
Reference80 articles.
1. Du, P., Samat, A., Waske, B., Liu, S., Li, Z.: Random forest and rotation forest for fully polarized SAR image classification using polarimetric and spatial features. ISPRS J. Photogramm. Remote Sens. 105, 38–53 (2015)
2. Samat, A., Gamba, P., Liu, S., Miao, Z., Li, E., Abuduwaili, J.: Quad-PolSAR data classification using modified random forest algorithms to map halophytic plants in arid areas. Int. J. Appl. Earth Obs. Geoinf. 73, 503–521 (2018)
3. Salehi, M., Sahebi, M.R., Maghsoudi, Y.: Improving the accuracy of urban land cover classification using Radarsat-2 PolSAR data. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 7(4), 1394–1401 (2013)
4. Hänsch, R., Hellwich, O.: Skipping the real world: classification of PolSAR images without explicit feature extraction. ISPRS J. Photogramm. Remote Sens. 140, 122–132 (2018)
5. Li, S., Wu, H., Wan, D., Zhu, J.: An effective feature selection method for hyperspectral image classification based on genetic algorithm and support vector machine. Knowl.-Based Syst. 24(1), 40–48 (2011)
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