A Convolutional Neural Network model created using PyTorch library over the MNIST dataset to recognize handwritten digits .

The C++ neural network for handwritten digit recognition with online demo

This task of digit recognition is done using Hidden Markov Model using Speech signal as input. This model is written in C++ and is trained on custom-recorded digit dataset.

The handwritten digit recognition is the ability of computers to recognize human handwritten digits. It is a hard task for the machine because handwritten digits are not perfect and can be made with many different flavors. The handwritten digit recognition is the solution to this problem which uses the image of a digit and recognizes the digit p…

a Java project to classify images of digits

Uma interface que permite desenhar um digito e que reconhece o digito utilizando um algoritmo de machine learning.

Implementation of MobileNet-V3 with pytorch and tested with Kaggle MNIST dataset

Classification algorithms to identify images by their bitmaps

Digits Recognize with Drawing(HTML Canvas). The Machine Learning Model can recognize any Handwritten Digit.

This is a project to solve SUDOKU using Computer Vision in python. Digit recognition model is trained on MNIST with accuracy>95%. Learned Machine Learning and Computer vision and implemented the concepts in this project.

Digit recognizer with 97.5% accuracy according to the Kagle scoring. I used different algorithms like; SVM, KNN, and Decision Tree

A digit recognition program which allows digits to be drawn by the user.

Program that detects digit like a human brain with layers of neurons.(Not machine learning)

digitRecognition

MNIST Digit Recognition repository offers a robust solution for recognizing handwritten digits using the MNIST dataset.

Digit recognition using Tensorflow.js

Mouse drawn live Digit Recognizer using Keras CNN and cv2 canvas

This repository contains a PyTorch-based model for handwritten digit recognition using the MNIST dataset.