Handwritten Character Recognition System Using Machine Learning And Deep Learning

Handwritten Character Recognition System Using Machine Learning And Deep Learning

Harsh Gupta1, Adarsh Singh2, Anurag Singh3, Dr. Laveena Sehgal4

1234Department of Information Technology

1234IIMT College of Engineering, Gretaer Noida, UP, India

harshgupta5989@gmail.com ,

Abstract - This project focuses on developing a system that can recognize handwritten characters using machine learning and deep learning techniques. Handwritten character recognition helps convert written text into digital form, which is useful for document digitization and automation. The system uses image processing to clean and prepare the input, and a Convolutional Neural Network (CNN) model is trained to identify the characters. Well-known datasets like MNIST are used to train and test the model. The aim is to build an accurate and efficient system that can recognize various handwritten letters and numbers with high accuracy.

Keywords – MNIST and EMNIST Dataset, Artificial Intelligence, Machine Learning, Deep Learning, Convolutional Neural Network, Neural Network, Image Processing, Support Vector Machine.