<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tamás Sámuel Tasi</style></author><author><style face="normal" font="default" size="100%">M Hegedűs</style></author><author><style face="normal" font="default" size="100%">Péter Balázs</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">M Petrou</style></author><author><style face="normal" font="default" size="100%">A D Sappa</style></author><author><style face="normal" font="default" size="100%">A G Triantafyllidis</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Perimeter estimation of some discrete sets from horizontal and vertical projections</style></title><secondary-title><style face="normal" font="default" size="100%">IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">June 2012</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IASTED ACTA Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Crete, Greek</style></pub-location><pages><style face="normal" font="default" size="100%">174 - 181</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In this paper, we design neural networks to estimate the perimeter of simple and more complex discrete sets from their horizontal and vertical projections. The information extracted this way can be useful to simplify the problem of reconstructing the discrete set from its projections, which task is in focus of discrete tomography. Beside presenting experimental results with neural networks, we also reveal some statistical properties of the perimeter of the studied discrete sets.&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type><notes><style face="normal" font="default" size="100%">ScopusID: 84864772360doi: 10.2316/P.2012.778-017</style></notes></record></records></xml>