Handwritten Digit Recognition using Machine Learning and Deep Learning
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Updated
Mar 25, 2023 - Python
Handwritten Digit Recognition using Machine Learning and Deep Learning
✏️ ☁️ The easy way to integrate mathematical expressions handwriting recognition in your web app.
Using OpenCV in python to recognize digits in a scanned page of handwritten digits.
Handwritten digit recognition with MNIST & Keras
Extract and solve sudoku from an image using Computer Vision and Deep Learning
Real time MNIST digit recognition with OpenCV and Support Vector Machine (SVM) algorithm.
Hand Written Digit Recognition
Implemented Convolutional Neural Network, LSTM Neural Network, and Neural Network From Scratch in Python Language.
Convert hand written mathematical expressions and formula to Latext using Machine Learning
Handwritten Digit Recognition Using Convolutional Neural Network by Python
🏆 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.
A computer vision project, based on cimg library and svm training, to classify handwriting number.
🎰Handwritten digit recognition application implemented by TensorFlow2 + Keras and Flask.
Handwriting Recognition using ML.NET
This project demonstrates Handwritten digit recognition using Deep Learning
During this Online Coding Internship, I have worked on projects related to Data Analytics and Machine Learning.
This project offers an efficient method for identifying and recognizing handwritten text from images. Using a Convolutional Recurrent Neural Network (CRNN) for Optical Character Recognition (OCR), it effectively extracts text from images, aiding in the digitization of handwritten documents and automated text extraction.
Handwritten Digit Recognition Using Random Forest
Handwritten digit classifier with deep learning
Recognize handwritten multi-digit numbers using a CRNN model trained with synthetic data.
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