Researchers at the University of Sfax, in Tunisia, have recently developed a new method to recognize handwritten characters and symbols in online scripts. Their technique, presented in a paper pre-published on arXiv, has already achieved remarkable performance on texts written in both the Latin and Arabic alphabet.
In recent years, researchers have created neural network-based architectures that can tackle a variety of tasks, including image classification, face recognition, natural language processing (NLP), and many more. Handwriting recognition systems are computer tools that are specifically designed to recognize characters and other hand-written symbols in a similar way to humans.
In their early years of life, in fact, human beings innately develop the ability to understand different types of handwriting by identifying specific characters both individually and when grouped together. Over the past decade or so, many studies have tried to replicate this ability in computer systems, as this would ultimately enable more advanced and automatic analyses of handwritten texts.
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