Robust vision-based features and classification schemes for offline handwritten digit recognition

Handwritten digits recognition using a Feedforward Neural Network

Convolutional Neural Network is used for handwritten digit recognition. The standard MNIST data set is used along with the MATLAB CNN Toolbox

This project demonstrates Handwritten digit recognition using Deep Learning.

📝 Using plain basic neural network to classify handwritten digits.

Classify images using Convolutional Neural Networks

Classifying Handwritten Digits Using Multiclass Logistic Regression And SVM

FeedForward Neural Networks Library ifrom scratch implemented using CUDA and vc++, With simple example application for MNIST dataset implementation with 97.82% Accuracy

A computer vision project, based on cimg library and svm training, to classify handwriting number.

A random forest classifier to recognize handwritten digits

An android app demoing machine learning on mobile.

This is a Machine Learning project based on Convolutional Neural Network (CNN) & Dense Neural Network(DNN). I trained the model using MNIST data-set and used TensorFlow as a training back-end. Used mostly Keras ( wrapper of Tensorflow) to get the HDF5 output. Then convert the .h5 file into .mlmodel which can be used in xcode.

JavaScript handwritten digits recognition. Try it -->

A modified extractor for the CROHME handwritten math symbols dataset.

Module to recognize handwritten digits using Neural Networks

KNN classifier

Handwritten digit classifier with deep learning

Deep learning Hello World - Recognizing handwritten digits with Keras.

Contains assignments I did in ML course