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           <title>WINGS morphology</title>
           <shortName>WINGSMorphot</shortName>
           <identifier>ivo://ia2.inaf.it/hosted/wings/cone/morphot</identifier>
           <curation>
              <publisher>IA2</publisher>
              <creator>
                 <name>IA2</name>
              </creator>
              <contact>
                 <name>Alessia Moretti</name>
                 <email>alessia.moretti@oapd.inaf.it</email>
              </contact>
           </curation>
           <content>
              <subject>galaxies morphology catalog</subject>
              <description>The catalogue contains a total number of ~39 900 galaxies, for which we provide the automated estimates of the morphological type, applying
        the purposely devised tool MORPHOT to the V-band WINGS imaging. The used tool is non-parametric and fully empirical. In particular, MORPHOT exploits 21 morphological diagnostics, directly and easily computable from the galaxy image, to provide two independent classifications: one based on a maximum likelihood (ML), semi- analytical technique and the other one on a neural network (NN) machine. A suitably selected sample of &amp;#8764;1000 visually classified WINGS galaxies is used to calibrate the diagnostics for theML estimator and as a training set in the NN machine. The final morphological estimator combines the two techniques. (http://adsabs.harvard.edu/abs/2012MNRAS.420..926F)</description>
              <referenceURL>http://web.oapd.inaf.it/wings/</referenceURL>
              <type>Catalog</type>
              <contentLevel>Research</contentLevel>
           </content>
           <rights>public</rights>
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                 <accessURL use="base">http://ia2-vo.oats.inaf.it:8080/ivoa/resources/cone/8?</accessURL>
              </interface>
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