Nowadays, there is a huge amount of Historical Arabic Documents (HAD) in the national
libraries and archives around the world. Analyzing this type of data manually is a difficult and …

This paper presents a digital image dataset of historical handwritten birth records stored in
the archives of several parishes across Sweden, together with the corresponding metadata …

Deep learning is a form of hierarchical learning, it consists of multiple layers of
representations that gradually transform data into high level concepts. Deep learning has …

In this paper we present, the Radial Descriptor Graph, a novel approach to compare pictorial
representation of handwritten text, which is based on the radial descriptor. To build a radial …

Word spotting in handwritten documents is challenging due to the high intra-class and inter-
class variability of handwritten forms. This paper addresses the word spotting problem in the …

In this paper, we present a sub-word recognition method for historical Arabic manuscripts,
using convolutional neural networks. We investigate the benefit of extending training set with …

We propose a pyramid-based method for keyword spotting in historical document images.
The documents are represented by a scale-space pyramid of their features. The search for a …

In this paper, we present a novel scheme for subdividing a pictorial representation of a word
or word-part into a sequence of blobs, that resemble the stroke representing the word. These …