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Most of the existed scene classification methods classify the scenes ignoring the semantic ground objects for high spatial resolution imagery. Though lots of methods are proposed to recognize the objects, there are lack of methods modeling the spatial relationship between objects for scene classification. Besides, the frequency vector of the semantic objects in the scenes is inadequate to model the...
Scene classification has been studied to allow us to semantically interpret high spatial resolution (HSR) remote sensing imagery. The bag-of-visual-words (BOVW) model is an effective method for HSR image scene classification. However, the traditional BOVW model only captures the local patterns of images by utilizing local features. In this letter, a local–global feature bag-of-visual-words scene classifier...
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