✏️ ☁️ The easy way to integrate mathematical expressions handwriting recognition in your web app.
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Updated
Jan 4, 2021 - JavaScript
✏️ ☁️ The easy way to integrate mathematical expressions handwriting recognition in your web app.
Handwritten Digit Recognition using Machine Learning and Deep Learning
Using OpenCV in python to recognize digits in a scanned page of handwritten digits.
Handwritten digit recognition with MNIST & Keras
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🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.
Hand Written Digit Recognition
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🎰Handwritten digit recognition application implemented by TensorFlow2 + Keras and Flask.
Real time MNIST digit recognition with OpenCV and Support Vector Machine (SVM) algorithm.
Implemented Convolutional Neural Network, LSTM Neural Network, and Neural Network From Scratch in Python Language.
The purpose of this project is to take handwritten digits as input, process the digits, train the neural network algorithm with the processed data, to recognize the pattern and successfully identify the test digits. The popular MNIST dataset is used for the training and testing purposes. The IDE used is MATLAB
A computer vision project, based on cimg library and svm training, to classify handwriting number.
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A modified extractor for the CROHME handwritten math symbols dataset.
Recognize Handwritten Digits - A Simple Web App
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