@Misc{FranciscoCruz2018,
author="Francisco Cruz
and Oriol Ramos Terrades",
title="A probabilistic framework for handwritten text line segmentation",
year="2018",
optkeywords="Document Analysis",
optkeywords="Text Line Segmentation",
optkeywords="EM algorithm",
optkeywords="Probabilistic Graphical Models",
optkeywords="Parameter Learning",
abstract="We successfully combine Expectation-Maximization algorithm and variationalapproaches for parameter learning and computing inference on Markov random fields. This is a general method that can be applied to many computervision tasks. In this paper, we apply it to handwritten text line segmentation.We conduct several experiments that demonstrate that our method deal withcommon issues of this task, such as complex document layout or non-latinscripts. The obtained results prove that our method achieve state-of-theart performance on different benchmark datasets without any particular finetuning step.",
optnote="DAG; 600.097; 600.121",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=3253), last updated on Thu, 28 Jan 2021 10:28:05 +0100"
}