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I would look at table 1 of the original paper. While you're reading the alogorithm, try to really focus on Step 2 when you get to it. In summary, each feature is used to train it's own classifier. So in your example, the calculated features X1, X2, ... Xn you describe coorespond to apply some set of feature transforms f_1, f_2, ... f_n to a single image. ...


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There are two related problems for images Semantic segmentation, where you need to assign each pixel on the image some class. I.e. you have a satellite image and want to segmentate roads/forests/fields and so on Objects detection, where you need to detect different types of objects and draw a bounding box for each. I.e. there is a popular dataset MSCOCO for ...


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