All subsequently described nodes essentially require a labeling as determined with the nodes introduced in the previous Section 3.6. Based on that they all produce a data table where basically each row corresponds to exactly one segment in the original labelings. The outcome of the nodes differ in terms of the segment-information they contain. The Segment Cropper-node just extracts either the bitmask of the segments, or, if an additional image column is provided, the image patch underneath the according segment. The Segment Feature- and Image Segment Feature-node in turn additionally allow one to calculate certain characteristics (called features, a vector of discriminative
13
numbers) for each segment individually. The Segment Features-nodes uses the labeling information exclusively, the Image Segment Features-node determines the features for a segment using the underlying images (hence, an additional image column is required).
All subsequently described nodes essentially require a labeling as determined with the nodes introduced in the previous Section 3.6. Based on that they all produce a data table where basically each row corresponds to exactly one segment in the original labelings. The outcome of the nodes differ in terms of the segment-information they contain. The Segment Cropper-node just extracts either the bitmask of the segments, or, if an additional image column is provided, the image patch underneath the according segment. The Segment Feature- and Image Segment Feature-node in turn additionally allow one to calculate certain characteristics (called features, a vector of discriminative13numbers) for each segment individually. The Segment Features-nodes uses the labeling information exclusively, the Image Segment Features-node determines the features for a segment using the underlying images (hence, an additional image column is required).
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