Feature selection is generally considered a very important step in any pattern recognition
process. Its aim is that of reducing the computational cost of the classification task, in an …

Recent theoretical and empirical work in statistical machine learning has demonstrated the
potential of learning algorithms for deep architectures, ie, function classes obtained by …

In the field of manuscript studies (palaeography and codicology), a particularly interesting
case is the study of highly standardized handwriting and book typologies. In such cases, the …

In this paper, a process of expansion of the training set by synthetic generation of
handwritten uppercase letters via deformations of natural images is tested in combination …

A robust method for plate segmentation in a License Plate Recognition (LPR) system is
presented, designed to work in a wide range of acquisition conditions, including unrestricted …

In handwritten character recognition, the rejection of extraneous patterns, like image noise,
strokes or corrections, can improve significantly the practical usefulness of a system. In this …

Recent theoretical and empirical work in statistical machine learning has demonstrated the
importance of learning algorithms for deep architectures, ie, function classes obtained by …

Although screening mammography is widely used for the detection of breast tumors, it is
difficult for a radiologist to interpret correctly a mammogram. It is possible to improve this task …

In the paper we consider the problem of continuous handwriting segmentation into
individual characters. The ultimate aim is to create the set of isolated character images used …

This paper proposes a new feature representation method based on the construction of a
Confidence Matrix (CM). This representation consists of posterior probability values …