AIMC Topic: Handwriting

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ET-Network: A novel efficient transformer deep learning model for automated Urdu handwritten text recognition.

PloS one
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...

Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination.

Sensors (Basel, Switzerland)
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...

Self-Adhesive, Anti-Freezing MXene-Based Hydrogel Strain Sensor for Motion Monitoring and Handwriting Recognition with Deep Learning.

ACS applied materials & interfaces
Flexible strain sensors based on self-adhesive, high-tensile, super-sensitive conductive hydrogels have promising application in human-computer interaction and motion monitoring. Traditional strain sensors have difficulty in balancing mechanical stre...

Handwriting Evaluation Using Deep Learning with SensoGrip.

Sensors (Basel, Switzerland)
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...

HUTNet: An Efficient Convolutional Neural Network for Handwritten Uchen Tibetan Character Recognition.

Big data
Recognition of handwritten Uchen Tibetan characters input has been considered an efficient way of acquiring mass data in the digital era. However, it still faces considerable challenges due to seriously touching letters and various morphological feat...

Automatic Gender and Age Classification from Offline Handwriting with Bilinear ResNet.

Sensors (Basel, Switzerland)
This work focuses on automatic gender and age prediction tasks from handwritten documents. This problem is of interest in a variety of fields, such as historical document analysis and forensic investigations. The challenge for automatic gender and ag...

Machine-Learning Assisted Handwriting Recognition Using Graphene Oxide-Based Hydrogel.

ACS applied materials & interfaces
Machine-learning assisted handwriting recognition is crucial for development of next-generation biometric technologies. However, most of the currently reported handwriting recognition systems are lacking in flexible sensing and machine learning capab...

A Smart Pen Based on Triboelectric Effects for Handwriting Pattern Tracking and Biometric Identification.

ACS applied materials & interfaces
The rapid development of artificial intelligence places high demands on human-machine interfaces. Various types of huma-machine interfaces have been implemented, including smart keyboards, electronic skins, and wearable motion sensors. Handwriting be...

Deep-Learning-Based Character Recognition from Handwriting Motion Data Captured Using IMU and Force Sensors.

Sensors (Basel, Switzerland)
Digitizing handwriting is mostly performed using either image-based methods, such as optical character recognition, or utilizing two or more devices, such as a special stylus and a smart pad. The high-cost nature of this approach necessitates a cheap...

Kurdish Handwritten character recognition using deep learning techniques.

Gene expression patterns : GEP
Handwriting recognition is regarded as a dynamic and inspiring topic in the exploration of pattern recognition and image processing. It has many applications including a blind reading aid, computerized reading, and processing for paper documents, mak...