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<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprs-archives-XLII-2-W12-17-2019</article-id>
<title-group>
<article-title>THE PROCEDURES OF VISUAL ANALYSIS FOR MULTIDIMENSIONAL DATA VOLUMES</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Bondarev</surname>
<given-names>A. E.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Keldysh Institute of Applied Mathematics RAS, 125047 Miusskaya sq. 4, Moscow, Russia</addr-line>
</aff>
<pub-date pub-type="epub">
<day>09</day>
<month>05</month>
<year>2019</year>
</pub-date>
<volume>XLII-2/W12</volume>
<fpage>17</fpage>
<lpage>21</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2019 A. E. Bondarev</copyright-statement>
<copyright-year>2019</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
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<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLII-2-W12/17/2019/isprs-archives-XLII-2-W12-17-2019.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLII-2-W12/17/2019/isprs-archives-XLII-2-W12-17-2019.pdf</self-uri>
<abstract>
<p>The paper is devoted to problems of visual analysis of multidimensional data sets using an approach based on the construction of elastic maps. This approach is quite suitable for processing and visualizing of multidimensional datasets. The elastic maps are used as the methods of original data points mapping to enclosed manifolds having less dimensionality. Diminishing the elasticity parameters one can design map surface which approximates the multidimensional dataset in question much better. Then the points of dataset in question are projected to the map. The extension of designed map to a flat plane allows one to get an insight about the structure of multidimensional dataset. The paper presents the results of applying elastic maps for visual analysis of multidimensional data sets of medical origin. Previously developed data processing procedures are applied to improve the results obtained - pre-filtering of data, removal of separated clusters (flotation), quasi-Zoom.</p>
</abstract>
<counts><page-count count="5"/></counts>
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