preprints.org > computer science and mathematics > artificial intelligence and machine learning > doi: 10.20944/preprints202312.1301.v1

Preprint Essay Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 16 December 2023 / Approved: 18 December 2023 / Online: 18 December 2023 (13:46:31 CET)

Machine learning is a fundamental aspect of artificial intelligence that involves the development of algorithms and models that allow computers to learn and make predictions or decisions without explicit programming. With the development of neural networks, back-propagation algorithms and deep learning, machine learning has made breakthroughs in the fields of image recognition, natural language processing and handwriting recognition using machine learning techniques. The advent of deep learning has revolutionized the field of handwriting recognition, using convolutional neural networks, recurrent neural networks, and sequence-to-sequence models to provide solutions that go beyond machine learning methods and significantly improve the accuracy and robustness of handwriting recognition systems. But challenges remain, including the need for large labelled datasets, computational resources and addressing potential biases. As research in deep learning techniques continues to drive handwriting recognition closer towards realisability, machine learning approaches remain at the forefront.

Handwriting recognition; Machine learning (ML); Deep learning; Transfer learning strategy; Handwritten datasets 

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

* All users must log in before leaving a comment