Abstract: This paper explores the application of deep learning algorithms, particularly Convolutional Neural Networks (CNNs), for Arabic handwritten digit recognition. The dataset used in this study ...

Bangla Handwritten Character Recognition (BHCR) remains challenging due to complex alphabets, and handwriting variations. In this study, we present a comparative evaluation of three deep learning ...

Learn how to build a digit recognition model from scratch using PyTorch! This beginner-friendly deep learning project walks you through loading the MNIST dataset, creating a neural network, training ...

The Dad Letter Project is described as a "hug, but on paper," its website said. Beginning in the fourth grade, 30-year-old Rosie Paulik said she grew up receiving countless handwritten letters from ...

This project implements a CNN-based image classification model using the MNIST dataset to recognize handwritten digits from 0 to 9. It is built using TensorFlow, trained in Google Colab, and ...

Abstract: Handwritten digit recognition plays a crucial role in applications like automated form processing and character recognition software. This study explores how well the traditional K-Nearest ...

First, we are using the full SVHN dataset, this dataset needs to be prepared, it contains multiple classes for folders, etc. the key to dealing with it is to be able to extract the images' ...