Handwritten Character Recognition Using Machine Learning

Within the domain of pattern recognition, the automated identification of handwritten characters or symbols presents a complex handwriting recognition challenges. In this paper, a novel methodology is presented, which employs machine learning techniques to achieve accurate and efficient handwritten character recognition. The proposed method utilizes artificial neural networks (ANN), specifically convolutional neural networks (CNNs), to train a model capable of accurately recognizing and classifying handwritten characters. Experimental results demonstrate that the proposed approach achieves an impressive accuracy of 98.6% on a standard dataset. The high accuracy achieved demonstrates the effectiveness and feasibility of machine learning algorithms for handwriting recognition tasks and opens up possibilities for various applications in areas such as document analysis, optical character recognition and handwriting-based interfaces. increase.