No vowels after here
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Updated
Jan 4, 2020 - Java
No vowels after here
This open source project is made for Autistic People who has difficulties in writing letters.
A machine learning project for letter recognition using SVM, KNN, and Decision Tree, Random Forest, and Naive Bayes algorithms. Includes data preprocessing, model training, evaluation, and visualization, and research report.
Letter naming fluency is a great indicator of risk and a strong predictor of reading success for young students. This app generates lists of letters that educators can use in the classroom for this important assessment.
TensorFlow/Keras-based Russian cursive letter recognition
This project consist of recognizing correct letters using machine learning algorithms namely XGBoost and KNN
📺 Letter recognition [👨🏫 Teacher: Киселев Александр Викторович] {6️⃣ Semester} (Artificial intelligence)
Alphabet recognition
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Android TensorFlow Lite-based app for my Russian cursive letter recognition ML model
This application allows you to practice writing letters and checks if you have written correct using neural networks
Structural Pattern Recognition home tasks: recognition of a line with letters containing noise and calculation of Levanstain distance between two lines of text
Experiment to create an artificial neural network in Typescript to recognize capital letters.
Classification d'images de lettres avec des algorithmes de Machine Learning
Clasificador de patrones matriciales de letras usando redes neuronales y perceptrón multicapa (MLP). TPI del año 2022 para la asignatura Inteligencia Artificial de la UTN FRRe
This project aims to implement AI-driven letter recognition using neural network libraries and the EMNIST dataset. By employing deep learning and data preprocessing, we seek to build a versatile system for accurately identifying letters in both handwritten and printed text, with applications in OCR and document digitization.
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