supervised classification of image

基本解釋

Our proposed CAAR algorithm is applied to supervised classification of image content and large-scale data mining, which is very effective.
將CAAR 分類新技術應用于有監(jiān)督的圖像內(nèi)容分類學習和大規(guī)模數(shù)據(jù)機器學習取得了很好的效果。
Extensive use of various image processing methods, including the supervised classification and the NDVI index, were made to identify the crops and salinity distribution.
利用監(jiān)督分類、NDVI指數(shù)等遙感影像處理方法，在黃河上游的寧夏青銅峽灌區(qū)開展識別作物及土壤鹽堿分布的應用研究。
While for terrace extraction, supervised classification has better result than unsupervised classification. The difference of total accuracy between two methods based on IKONOS image is more than 12%.
而對于IKONOS影像梯田提取，兩種分類結果精度相差12%以上，監(jiān)督分類結果明顯優(yōu)于非監(jiān)督分類結果。