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.

a Java project to classify images of digits

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…

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

Classification algorithms to identify images by their bitmaps

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

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

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

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.

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

Digit recognition using Tensorflow.js

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

This project is a handwritten digit classifier built with PyTorch and trained on the MNIST dataset. It uses a Convolutional Neural Network (CNN) to recognize digits from 0 to 9 with high accuracy. The project features a Streamlit web app that allows users to upload their own handwritten digit images and get real-time predictions.

digitRecognition

Mouse drawn live Digit Recognizer using Keras CNN and cv2 canvas

This project includes a 2 layer neural network and a perceptron, both of which were trained for classifying faces and digits.

In this Kaggle competition, your goal is to correctly identify digits from a dataset of tens of thousands of handwritten images.