Experimental approach for identifying building surface materials based on hyperspectral remote sensing imagery
Author:
Funder
the National Key Technologies R&D Program of China
the Key Project of Sichuan Provincial Education Department, China
Publisher
Zhejiang University Press
Subject
General Engineering
Link
http://link.springer.com/content/pdf/10.1631/jzus.A1700149.pdf
Reference24 articles.
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2. Chen, Y.S., Lin, Z.H., Zhao, X., et al., 2014. Deep learningbased classification of hyperspectral data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(6):2094–2107. http://dx.doi.org/10.1109/JSTARS.2014.2329330
3. Elnazir, R., Feng, X.Z., Cheng, Z., 2004. Satellite remote sensing for urban growth assessment in Shaoxing City- Zhejiang Province. Journal of Zhejiang University- SCIENCE, 5(9):1095–1101. http://dx.doi.org/10.1631/jzus.2004.1095
4. Fauvel, M., Tarabalka, Y., Benediktsson, J.A., et al., 2013. Advances in spectral-spatial classification of hyperspectral images. Proceedings of the IEEE, 101(3):652–675. http://dx.doi.org/10.1109/JPROC.2012.2197589
5. Fiumi, L., 2012. Surveying the roofs of Rome. Journal of Cultural Heritage, 13(3):304–313. http://dx.doi.org/10.1016/j.culher.2011.12.003
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