机译:利用偏振和空间特征对全极化SAR图像进行分类的随机森林和旋转森林
Nanjing Univ, State Adm Surveying Mapping & Geoinformat, Key Lab Satellite Mapping Technol & Applicat, Nanjing, Jiangsu, Peoples R China|Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing, Jiangsu, Peoples R China;
Nanjing Univ, State Adm Surveying Mapping & Geoinformat, Key Lab Satellite Mapping Technol & Applicat, Nanjing, Jiangsu, Peoples R China|Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing, Jiangsu, Peoples R China;
Free Univ Berlin, Dept Earth Sci, Berlin, Germany;
Univ Trent, Dept Informat Engn & Comp Sci, I-38100 Trento, Italy;
Univ Newcastle, Sch Civil Engn & Geosci, Newcastle Upon Tyne, Tyne & Wear, England;
Polarimetric SAR; Image classification; Textural feature; Morphological profiles; Ensemble learning; Random Forest; Rotation Forest;
机译:基于多特征组合和极端随机聚类森林的极化SAR图像分类
机译:基于多特征组合和极端随机聚类森林的极化SAR图像分类
机译:用于纳米管森林测量的光学标度极化设备:预测P带树干森林双基地极化SAR图像的机会
机译:基于极化SAR图像的城市区域在线随机森林分类
机译:用于气相色谱/差分移动光谱(GC / DMS)数据的特征提取和随机森林分类软件
机译:使用一般线性模型和时间序列Quad-Polarimetric SAR图像估算种植森林的生长茎体积
机译:基于多特征组合和极端随机聚类森林的极化SAR图像分类