Handwriting digits and character recognitions have become increasingly important in today’s digitized world. Different recognition systems have been developed or proposed to be used in different fields where high classification efficiency is needed. The handwriting recognition systems can be inspired by biological neural networks, which allow humans and animals to learn and model non-linear and complex relationships.
The human visual system is primarily involved whenever individuals are reading Handwriting characters, letters, words, or digits. A human can make sense of what they see based on what their brains have been taught, although everything is done unconsciously. The challenge of visual pattern recognition is only apparent to develop a computer system to read handwriting.
The main aim of this paper is to develop a model that will be used to read Handwriting digits, characters, and words from the image using the concept of Convolution Neural Network. The next sections will provide an overview of the related work, theoretical background, the architecture, methodology, experimental results, and conclusion.
Handwriting5
Handwriting Recognition using Artificial Intelligence Neural Network and Image Processing