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 ...

MNIST Digit Classifier - Deep Learning Web Application A handwritten digit classification system using Deep Neural Networks (DNN) deployed as an interactive Streamlit web application. Status: Ready to ...

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 ...

Introduction: The COVID-19 pandemic accelerated global online education, which faces “shallow learning” challenges. Deep learning is key to student competencies. Based on sociocultural theory, this ...

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 ...

Institute for Quantum Information & State Key Laboratory of High-Performance Computing, College of Computer, National University of Defense Technology, Changsha 410073, China ...