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Handwritten Digit Recognition Report by sahanafathima268 is a document available to read on EtoBox.

This project report details the development of a Handwritten Digit Recognition system using a Convolutional Neural Network (CNN) trained on the Extended MNIST (EMNIST) dataset. The CNN architecture includes multiple convolutional, pooling, and fully connected layers, achieving a test accuracy of 98.64% and demonstrating the effectiveness of deep learning techniques in image classification. The project provides a foundation for further applications in optical character recognition and suggests future enhance

Author

sahanafathima268

Language

EN