Scene categorization via contextual visual words

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A 2-D wavelet decomposition-based bag-of-visual-words model for land-use scene classification (2014, background): “…efficiently with various local interest point detectors (Lowe 2004; Mikolajczyk and Schmid 2004) or dense regions (Lazebnik, Schmid, and Ponce 2006; Qin and Yung 2010), and describes it with local descriptors (Mikolajczyk and Schmid 2005) among which affine invariant features (e.g. the…”
SIFT and color feature fusion using localized maximum-margin learning for scene classification (2011, methodology): “After transforming the image into Lab color space, the ROI is divided into 4x4 blocks.”
Large patch convolutional neural networks for the scene classification of high spatial resolution imagery (2016, background): “The complexity of HSR-RS scenes is increased due to the difference in illumination and the various scales of HSR-RS image scenes.(6,7) The HSR-RS scene commonly refers to a subpart of a whole remote-sensing image, which carries comparatively clear semantic information about the”
Support Distribution Machines (2012, background): “Qin and Yung (2010a) proposed another way to encode the spatial dependencies of patches into the visual words and achieved 90 .”