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This will facilitate the interpretation of features in the structures being published and in the figures being displayed.
Moreover, NPR techniques usually are meant to provide expressive, flexible visual representations, which are characterized by the use of randomness and arbitrary interpretation of features being drawn, rather than total adherence to realistic properties [2].
Furthermore, especially multi-resolution decomposition produces an important loss on the potential interpretation of features and signals, regardless of the remarkable increase of the statistical significance of the features reported using such analyses.
During the development of the visualizations, the clinicians often had issues with the meaning and interpretation of features considered important and insightful by the researchers; the clinicians considered them unclear and ambiguous, or did not understand their significance.
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Careful attention has been paid to artefact testing of the non-rigid registration method used, and the importance of this registration for the quantitative interpretation of feature intensities and positions is evaluated.
Features found to result in maximally predictive models are not consistent across learning techniques, suggesting care should be taken in the interpretation of feature relevance.
Materials such as mirror and pocket stereoscopes were employed for stereo viewing during visual interpretations of features on hardcopy pairs of aerial photos.
Next visual interpretations of features on the aerial photographs were made based on the shade, shape, size, tone, pattern, texture and location of the features from aerial photos (1964 and 1986) using a mirror stereoscope (Ermias et al. 2013).
This resulted in deeper analysis to produce second order themes and the development of new interpretations of features of recruitment and retention of OTs and PTs in rural areas.
In the framework we employed, not only do the statistical tests help reduce search space by focusing on significant features for feature selection in classification, but they also provide ground for biologically meaningful interpretations of features as we have discussed in the section of feature significance.
(2) The Forward selection is performed using an OP-ELM classifier to find a good features set, from which follows a possible interpretation of the features or the typical classification for steganalysis.
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