  In this paper, we investigate the use of Convolutional Neural Networks for
counting the number of records in historical handwritten documents. With this
work we demonstrate that training the networks only with synthetic images
allows us to perform a near perfect evaluation of the number of records printed
on historical documents. The experiments have been performed on a benchmark
dataset composed by marriage records and outperform previous results on this
dataset.
