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Handwriting

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A Machine Learning and Deep Learning Approach for Recognizing Handwritten Digits.

Computational intelligence and neuroscience
Optical character recognition (OCR) can be a subcategory of graphic design that involves extracting text from images or scanned documents. We have chosen to make unique handwritten digits available on the Modified National Institute of Standards and ...

Leveraging ShuffleNet transfer learning to enhance handwritten character recognition.

Gene expression patterns : GEP
Handwritten character recognition has continually been a fascinating field of study in pattern recognition due to its numerous real-life applications, such as the reading tools for blind people and the reading tools for handwritten bank cheques. Ther...

Dysgraphia disorder forecasting and classification technique using intelligent deep learning approaches.

Progress in neuro-psychopharmacology & biological psychiatry
Writing abilities are impacted by dysgraphia, a condition of learning disability. It might be challenging to diagnose dysgraphia at an initial point of a child's upbringing. Problematic abilities linked to Dysgraphia difficulties that is utilized in ...

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...

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...

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...

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...

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...

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...

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...