Handwriting learning disabilities, such as dysgraphia, have a serious negative impact on children's academic results, daily life and overall well-being. Early detection of dysgraphia facilitates an early start of targeted intervention. Several studie...
Handwritten Arabic character recognition has received increasing research interest in recent years. However, as of yet, the majority of the existing handwriting recognition systems have only focused on adult handwriting. In contrast, there have not b...
BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disease that is not easily detected in the early stage. Handwriting and walking have been shown to be potential indicators of cognitive decline and are often affected by AD.
Automatic Urdu handwritten text recognition is a challenging task in the OCR industry. Unlike printed text, Urdu handwriting lacks a uniform font and structure. This lack of uniformity causes data inconsistencies and recognition issues. Different wri...
In an era marked by escalating concerns about digital security, biometric identification methods have gained paramount importance. Despite the increasing adoption of biometric techniques, keystroke dynamics analysis remains a less explored yet promis...
Conductive hydrogels are widely used in flexible sensors owing to their adjustable structure, good conductivity, and flexibility. The performance of excellent mechanical properties, high sensitivity, and elastic modulus compatible with human tissues ...
With over 55 million people globally affected by dementia and nearly 10 million new cases reported annually, Alzheimer's disease is a prevalent and challenging neurodegenerative disorder. Despite significant advancements in machine learning technique...
Accurate air-writing recognition is pivotal for advancing state-of-the-art text recognizers, encryption tools, and biometric technologies. However, most existing air-writing recognition systems rely on image-based sensors to track hand and finger mot...
The combination of wearable sensors with machine learning enables intelligent perception in human-machine interaction and healthcare, but achieving high sensitivity and a wide working range in flexible strain sensors for signal acquisition and accura...
Journal of the World federation of orthodontists
39232889
BACKGROUND: The purpose of this study was to compare the success of various convolutional neural network (CNN) models trained with handwriting samples in predicting patient cooperation.