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Digit recognition with deep learning — PyTorch beginner project

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 ...
Frontiers

Enhancing Bangla handwritten character recognition using Vision Transformers, VGG-16, and ResNet-50: a performance analysis

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 ...
IEEE

Handwritten Devanagari Numeral Recognition Using Deep Learning

Abstract: Handwritten Roman characters and numbers have been intensively examined in the past several decades, with satisfactory results. The Devanagari script, however, does not fit this description.
GitHub

A Deep Learning project for handwritten digit recognition using CNN and TensorFlow

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 ...
GitHub

This is a project for handwritten digits recognition system using image recognition deep learning.

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' ...
IEEE

Handwritten Digit Recognition Based on Deep Learning Algorithms

Abstract: In the digital age, handwritten digit recognition plays a crucial role in various automation systems, ranging from simple form data automation to complex security systems. Deep learning, ...