In recent times, many research projects and experiments target machines that automatically
recognize handwritten characters, but most of them are done in Latin. Recognizing …

Offline Arabic Handwriting Recognition (OAHR) has recently become instrumental in the
areas of pattern recognition and image processing due to its application in several fields …

Handwritten character recognition is a computer-vision-system problem that is still critical
and challenging in many computer-vision tasks. With the increased interest in handwriting …

Handwriting recognition refers to recognizing a handwritten input that includes character (s)
or digit (s) based on an image. Because most applications of handwriting recognition in real …

In recent years, Deep neural networks (DNNs) have achieved great success in sequence
modeling. Several deep models have been used for enhancing Handwriting Text …

Alzheimer's disease (AD) primarily impacts a distinct demographic, specifically individuals
who are 60 years old and older, predominantly affecting the elderly. AD is an emerging …

Although deep learning techniques have achieved promising results in several fields
including healthcare, monitoring, and smart cities, their application in handwriting …

Recognition of handwritten words is a widely used system in the modern world that remains
a significant challenge. Traditional machine learning techniques require creative …

Alzheimer's disease (AD) is a condition that predominantly affects a specific age group,
namely the elderly, individuals aged 60 years and above. AD is an emerging neurological …

Cursive handwriting recognition (CHWR) is an interesting area of research as it has a wide
range of applications but lacks an accurate approach to provide better results due to its …