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唐淑兰等:结合多尺度分割和随机森林的变质矿物提取 179 Sens,2019,23(1:125 Geosci,.2020,52(4):451 (游永发,王思远,王斌,等.高分辨率遥感影像建筑物分级提取 [18]Zhang L,Liu Z,Ren T W,et al.Identification of seed maize fields 遥感学报,2019,23(1):125) with high spatial resolution and multiple spectral remote sensing [13]Li J Y,Zhao YK,Xue Z E,et al.A survey of model compression using random forest classifier.Remote Sens,2020,12(3):362 for deep neural networks.ChinJEng,2019,41(10):1229 [19]Zhu J J,Fan X T,Du X P.Geometric feature representation and (李江昀,赵义凯,薛卓尔,等.深度神经网络模型压缩综述.工 building extraction based on geometric features.J Appl Sci,2015, 程科学学报,2019,41(10):1229) 33(1:9 [14]Cracknell M J,Reading A M.Geological mapping using remote (朱俊杰,范湘涛,杜小平几何特征表达及基于几何特征的建 sensing data:A comparison of five machine leaming algorithms, 筑物提取.应用科学学报,2015,33(1):9) their response to variations in the spatial distribution of training [20]Masoumi F,Eslamkish T,Abkar AA,et al.Integration of spectral, data and the use of explicit spatial information.Compu Geosci, thermal,and textural features of ASTER data using random forests 2014,63:22 [15]Harris J.R,He JX.Rainbird R,et al.A comparison of different classification for lithological mapping.J Afric Earth Sci,2017, 129:445 remotely sensed data for classifying bedrock types in Canada's [21]Pournamdari M,Hashim M,Pour A B.Spectral transformation of arctic:application of the robust classification method and random forests.Geosci Can,2014,41(4):557 ASTER and Landsat TM bands for lithological mapping of Soghan [16]Hossain M D,Chen D M.Segmentation for object-based image ophiolite complex,South Iran.Ady Space Res,2014,54(4):694 analysis (OBIA):A review of algorithms and challenges from [22]Zhang B.He B B.Multi-scale segmentation of high-resolution remote sensing perspective.ISPRSJ Photogramm Remote Sens. remote sensing image based on improved watershed 2019,150:115 transformation.J Geo-Inf Sci,2014,16(1):142 [17]Diaz G F,Ortiz J M,Silva J F,et al.Variogram-based descriptors (张博,何彬彬.改进的分水岭变换算法在高分辨率遥感影像多 for comparison and classification of rock texture images.Math 尺度分割中的应用.地球信息科学学报,2014,16(1):142)Sens, 2019, 23(1): 125 (游永发, 王思远, 王斌, 等. 高分辨率遥感影像建筑物分级提取. 遥感学报, 2019, 23(1):125) Li J Y, Zhao Y K, Xue Z E, et al. A survey of model compression for deep neural networks. Chin J Eng, 2019, 41(10): 1229 (李江昀, 赵义凯, 薛卓尔, 等. 深度神经网络模型压缩综述. 工 程科学学报, 2019, 41(10):1229) [13] Cracknell  M  J,  Reading  A  M.  Geological  mapping  using  remote sensing  data:  A  comparison  of  five  machine  learning  algorithms, their  response  to  variations  in  the  spatial  distribution  of  training data  and  the  use  of  explicit  spatial  information. Comput Geosci, 2014, 63: 22 [14] Harris J. R, He J X, Rainbird R, et al. A comparison of different remotely  sensed  data  for  classifying  bedrock  types  in  Canada ’s arctic: application of the robust classification method and random forests. Geosci Can, 2014, 41(4): 557 [15] Hossain  M  D,  Chen  D  M.  Segmentation  for  object-based  image analysis  (OBIA):  A  review  of  algorithms  and  challenges  from remote  sensing  perspective. ISPRS J Photogramm Remote Sens, 2019, 150: 115 [16] Diaz G F, Ortiz J M, Silva J F, et al. Variogram-based descriptors for  comparison  and  classification  of  rock  texture  images. Math [17] Geosci, 2020, 52(4): 451 Zhang L, Liu Z, Ren T W, et al. Identification of seed maize fields with  high  spatial  resolution  and  multiple  spectral  remote  sensing using random forest classifier. Remote Sens, 2020, 12(3): 362 [18] Zhu J J, Fan X T, Du X P. Geometric feature representation and building extraction based on geometric features. J Appl Sci, 2015, 33(1): 9 (朱俊杰, 范湘涛, 杜小平. 几何特征表达及基于几何特征的建 筑物提取. 应用科学学报, 2015, 33(1):9) [19] Masoumi F, Eslamkish T, Abkar A A, et al. Integration of spectral, thermal, and textural features of ASTER data using random forests classification  for  lithological  mapping. J Afric Earth Sci,  2017, 129: 445 [20] Pournamdari M, Hashim M, Pour A B. Spectral transformation of ASTER and Landsat TM bands for lithological mapping of Soghan ophiolite complex, South Iran. Adv Space Res, 2014, 54(4): 694 [21] Zhang  B,  He  B  B.  Multi-scale  segmentation  of  high-resolution remote  sensing  image  based  on  improved  watershed transformation. J Geo-Inf Sci, 2014, 16(1): 142 (张博, 何彬彬. 改进的分水岭变换算法在高分辨率遥感影像多 尺度分割中的应用. 地球信息科学学报, 2014, 16(1):142) [22] 唐淑兰等: 结合多尺度分割和随机森林的变质矿物提取 · 179 ·
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