Authors : Gottipati Ajay; Srungavarapu Bhuvanesh Babu; Madala Narasimha Rao; Magam Satya Siva Krishna; Dr. M. D Gouse

Volume/Issue : Volume 9 - 2024, Issue 7 - July

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Google Scholar : https://tinyurl.com/379acjc9

Scribd : https://tinyurl.com/yaefnm62

DOI : https://doi.org/10.38124/ijisrt/IJISRT24JUL929

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

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Abstract : The capacity of a device to recognise and understand legible handwriting input from a variety of origins, including written material, snap shots, displays, and other electronics, is known as handwritten reputation. In this study, we investigate three classification algorithms: Support Vector Machines (SVM), K-Nearest_Neighbours (KNN), and Neural Networks for handwritten character recognition, and we will identify the best one among these three.

Keywords : Handwritten popularity, SVM, Neural Network, K-Nearest Neighbor;

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