Research on the High Resolution Remote Sensing Image Target Detection Based on Machine Learning
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-63136-8_39
Reference15 articles.
1. Liu, X., Li, Ya.: Research on classification method of medium resolution remote sensing image based on machine learning. In: Pan, G., Lin, H., Meng, X., Gao, Y., Li, Y., Guan, Q., Ding, Z. (eds.) Spatial Data and Intelligence: Second International Conference, SpatialDI 2021, Hangzhou, China, April 22–24, 2021, Proceedings, pp. 164–173. Springer International Publishing, Cham (2021). https://doi.org/10.1007/978-3-030-85462-1_15
2. Jia, Y.: A refined method of high-resolution remote sensing change detection based on machine learning for newly constructed building areas. Remote Sens. 13(8), 1507 (2021). https://doi.org/10.3390/rs13081507
3. Hu, Y., Che, T., Dai, L., et al.: Remote sensing snow depth fusion based on machine learning methods for the northern hemisphere. Remote Sens. 13(7), 1250 (2021)
4. Wang, T., Zhang, J., Li, T., et al.: Research on detection technology for the changes of buildings by high resolution remote sensing image. J. Phys. Conf. Ser. 1972(1), 012066 (7pp) (2021)
5. Feng, H.: Land-cover classification of high-resolution remote sensing image based on multi-classifier fusion and the improved Dempster-Shafer evidence theory. J. Appl. Remote Sens. 15(1) (2021)
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