<?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%">Arnaud Martin</style></author><author><style face="normal" font="default" size="100%">Christophe Osswald</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Experts Fusion and Multilayer Perceptron Based on Belief Learning for Sonar Image Classification</style></title><secondary-title><style face="normal" font="default" size="100%">3rd International Conference on Information and Communication Technologies: From Theory to Applications</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%"> 7-11 April 2008</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Damascus, Syria</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arnaud Martin</style></author><author><style face="normal" font="default" size="100%">Christophe Osswald</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Une nouvelle règle de combinaison répartissant le conflit - Applications en imagerie Sonar et classification de cibles Radar</style></title><secondary-title><style face="normal" font="default" size="100%">Traitement du Signal, Lavoisier</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><volume><style face="normal" font="default" size="100%">24</style></volume><pages><style face="normal" font="default" size="100%">71-82</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">2</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arnaud Martin</style></author><author><style face="normal" font="default" size="100%">Christophe Osswald</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Une nouvelle règle de combinaison répartissant le conflit - Applications en imagerie Sonar et classification de cibles Radar</style></title><secondary-title><style face="normal" font="default" size="100%">Revue Traitement du Signal</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><volume><style face="normal" font="default" size="100%">24</style></volume><pages><style face="normal" font="default" size="100%">71-82</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">2</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arnaud Martin</style></author><author><style face="normal" font="default" size="100%">Christophe Osswald</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Generalized proportional conflict redistribution rule applied to Sonar imagery and Radar targets classification</style></title><secondary-title><style face="normal" font="default" size="100%">Advances and Applications of DSmT for Information Fusion</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">11</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arnaud Martin</style></author><author><style face="normal" font="default" size="100%">Christophe Osswald</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Human Expert Fusion for Image Classification</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">DSmT</style></keyword><keyword><style  face="normal" font="default" size="100%">DST</style></keyword><keyword><style  face="normal" font="default" size="100%">Experts fusion</style></keyword><keyword><style  face="normal" font="default" size="100%">image classification</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2006</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">122-143</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In image classification, merging the opinion of several human experts is very important for different tasks such as the evaluation or the training. Indeed, the ground truth is rarely known before the scene imaging. We propose here different models in order to fuse the informations given by two or more experts. The considered unit for the classification, a small tile of the image, can contain one or more kind of the considered classes given by the experts. A second problem that we have to take into account, is the amount of certainty of the expert has for each pixel of the tile. In order to solve these problems we define five models in the context of the Dempster-Shafer Theory and in the context of the Dezert-Smarandache Theory and we study the possible decisions with these models.</style></abstract></record><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%">Christophe Osswald</style></author><author><style face="normal" font="default" size="100%">Arnaud Martin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Understanding the large family of Dempster-Shafer theory's fusion operators - a decision-based measure</style></title><secondary-title><style face="normal" font="default" size="100%">9th International Conference on Information Fusion</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10-13 July 2006</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Florence, Italy</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>