参考文献/References:
[1] SONG Jia, GAO Shaohua, ZHU Yunqiang, et al. A survey of remote sensing image classification based on CNNs[J]. Big earth data, 2019, 3(3):232-254.
[2] TU Bing, ZHANG Xiaofei, KANG Xudong, et al. Hyperspectral image classification via fusing correlation coefficient and joint sparse representation[J]. IEEE geoscience and remote sensing letters, 2018, 15(3):340-344.
[3] 杨帆, 王博. 基于决策树的遥感图像分类方法研究[J]. 测绘与空间地理信息, 2019, 42(7):1-4.YANG Fan, WANG Bo. Research of remote sensing image classification based on decision tree method[J]. Geomatics & spatial information technology, 2019, 42(7):1-4.
[4] FAUVEL M, TARABALKA Y, BENEDIKTSSON J A, et al. Advances in spectral-spatial classification of hyperspectral images[J]. Proceedings of the IEEE, 2013, 101(3):652-675.
[5] MELGANI F, BRUZZONE L. Classification of hyperspectral remote sensing images with support vector machines[J]. IEEE transactions on geoscience and remote sensing, 2004, 42(8):1778-1790.
[6] 王立国, 赵亮, 刘丹凤. SVM在高光谱图像处理中的应用综述[J]. 哈尔滨工程大学学报, 2018, 39(6):973-983.WANG Liguo, ZHAO Liang, LIU Danfeng. A review on the application of SVM in hyperspectral image processing[J]. Journal of Harbin Engineering University, 2018, 39(6):973-983.
[7] ZHOU Zhihua, LI Ming. Tri-training:exploiting unlabeled data using three classifiers[J]. IEEE transactions on knowledge and data engineering, 2005, 17(11):1529-1541.
[8] MA Ailing, ZHONG Yanfei, ZHAO Bei, et al. Semisupervised subspace-based DNA encoding and matching classifier for hyperspectral remote sensing imagery[J]. IEEE transactions on geoscience and remote sensing, 2016, 54(8):4402-4418.
[9] BENEDIKTSSON J A, PALMASON J A, SVEINSSON J R. Classification of hyperspectral data from urban areas based on extended morphological profiles[J]. IEEE transactions on geoscience and remote sensing, 2005, 43(3):480-491.
[10] ZHAN Ying, WU Kang, LIU Wei, et al. Semi-supervised classification of hyperspectral data based on generative adversarial networks and neighborhood majority voting[C]//IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium. Valencia, Spain, 2018.
[11] LI Wei, DU Qian. Gabor-filtering-based nearest regularized subspace for hyperspectral image classification[J]. IEEE journal of selected topics in applied earth observations and remote sensing, 2014, 7(4):1012-1022.
[12] BAJORSKI P. Statistical inference in PCA for hyperspectral images[J]. IEEE journal of selected topics in signal processing, 2011, 5(3):438-445.
[13] KUO B C, LI C H, YANG J M. Kernel nonparametric weighted feature extraction for hyperspectral image classification[J]. IEEE transactions on geoscience and remote sensing, 2009, 47(4):1139-1155.
[14] SHEN Linlin, JIA Sen. Three-dimensional Gabor wavelets for pixel-based hyperspectral imagery classification[J]. IEEE transactions on geoscience and remote sensing, 2011, 49(12):5039-5046.
[15] RAO R V, SAVSANI V J, VAKHARIA D P. Teaching-learning-based optimization:an optimization method for continuous non-linear large scale problems[J]. Information sciences, 2012, 183(1):1-15.
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