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As many of them provide data with considerable noise and distortions, detecting objects, for example, using canonical methods for range data segmentation or feature extraction, is complicated.
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For ranging data verification, a 200 m base line composed of 20 points with interval 10 m is designed, as shown in Fig. 5a.
Variance stabilization is very important for small data sets, although, as comparison shows, even for medium range data sets of 10 ÷ 30 samples, improvement can be significant.
The authors' method is based on a shape space vector derived from a statistical shape model for 3D range data.
Where species and subspecies status differed between host plant data and data on geographic range, we followed the nomenclature used for the geographic range data.
Mean score (SD) and range data for each of the eight domains are presented.
Several corrections for accurate ranging data are investigated.
When direct entry of data is used, the software uses prompts for out-of-range data and consistent terminology use.
For example, GPS-acoustic ranging data show that the horizontal displacement at a site c.
Hence the method is appropriate for direct use on range image data without re-sampling.
Initial data analysis will be conducted to assess for data quality including allowable ranges, data structure and errors.
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