Urban landcover classification from multispectral image data using optimized AdaBoosted random forests
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DOI: 10.1080/2150704x.2016.1274443
Abstract: ABSTRACT With an ever growing need to classify multispectral images, the accuracy of the classification becomes a matter of concern, especially when mapping heterogeneous environments such as urban areas. Not all of the features of… read more here.
Keywords: adaboosted random; random forests; multispectral image; classification ... See more keywords