The advent of recurrent neural networks for handwriting recognition marked an important
milestone reaching impressive recognition accuracies despite the great variability that we …

Handwriting has remained one of the most frequently occurring patterns that we come
across in everyday life. Handwriting offers a number of interesting pattern classification …

Abstract This paper proposes Convolve, Attend and Spell, an attention-based sequence-to-
sequence model for handwritten word recognition. The proposed architecture has three …

In recent years, Handwritten Text Recognition (HTR) has attracted widespread attention due
to its huge applications. HTR is the process of extracting handwritten text from an image and …

Sequence-to-sequence models have recently become very popular for tackling handwritten
word recognition problems. However, how to effectively integrate an external language …

In this paper, we present a model CNN based HMM for Arabic handwriting word recognition.
The HMM have proved a powerful to model the dynamics of handwriting. Meanwhile, the …

In this paper, we present a multi-stage HMM-based text recognition system for handwritten
Arabic. This system employs a novel way of representing Arabic characters by separating …

Deep learning models are considered a revolutionary learning paradigm in artificial
intelligence and machine learning, piquing the interest of image recognition and computer …

The area of offline handwritten text recognition (OHTR) has been widely researched in the
last decades, but it stills an important research problem. The OHTR system has an objective …

Distinguishing an Arabic handwritten text is a hard task because the Arabic word is
morphologically complex and the writing style from one model is highly variable, like the …