<?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%">Lena Maier-Hein</style></author><author><style face="normal" font="default" size="100%">Sven Mersmann</style></author><author><style face="normal" font="default" size="100%">Daniel Kondermann</style></author><author><style face="normal" font="default" size="100%">Bodenstedt, S.</style></author><author><style face="normal" font="default" size="100%">Sanchez, A.</style></author><author><style face="normal" font="default" size="100%">C. Stock</style></author><author><style face="normal" font="default" size="100%">Kenngott, H.</style></author><author><style face="normal" font="default" size="100%">Eisenmann, M.</style></author><author><style face="normal" font="default" size="100%">Speidel, S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Can masses of non-experts train highly accurate image classifiers? A crowdsourcing approach to instrument segmentation in laparoscopic images</style></title><secondary-title><style face="normal" font="default" size="100%">MICCAI</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>