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In this step, a probabilistic method is used to mine the relationship among semantic features, regions, and images automatically.
After the reader selected the features, regions of interest (ROI) of 40 × 40 pixels were extracted from the image.
All the features (regions of interest) selected by the best models were located in prefrontal cortex (PFC), anterior cingulate cortex, and parietal cortex.
After taking into account of the correlation between the binding sites and biologically related supporting features, regions coincide with strong supporting signals will become detectable by our method.
This study analyzed three main categories of annotations: genic and regulatory features, regions with conserved or evolutionary signatures, and chromatin states.
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salient feature regions.
(a) Pairwise comparison of local feature regions [13].
(b) Repeatability of local feature regions in input images.
Several local feature regions are extracted from four different images.
By applying this process to all local feature regions, a non-directed graph is obtained.
After fixing the feature regions, then it is processed distinctly using NSCT approach.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com