Predicting kannada digits and alphabets (40+classes) by voluntarily drawing them in real time using 3DPaint tool.

This project is a comprehensive solution for recognizing handwritten digits and text from images, with functionalities for training, testing, and usage, making it suitable for tasks like cheque amount verification and other handwritten text recognition applications.

Handwritten text recognition using CNN with EMNIST dataset

Preprocessing methods to enhance Tesseract-OCR in the case of printed text on difficult background, or handwritten text on lined/squared paper.

Zilla-64: A Bangla Handwritten Word Dataset Of 64 Districts Name of Bangladesh and Recognition Using Holistic Approach

Automate handwritten multiple-choice test grading with HMC-Grad, using a CNN trained in PyTorch on the EMNIST dataset and OpenCV for image processing. Input the correction key and the images of the answer sheets to receive each one's correctness and score, along with item and score analysis, in CSV and XLSX formats, and the annotated images as JPG.

Meetei Mayek Character Recognition: Hybrid CNN+LSTM model for Meetei Mayek script recognition.

ML Codefest

🔢🖋️ ProjetCHROME - Reconnaissance de formules mathématiques manuscrites. Ce projet transforme des expressions mathématiques écrites à la main (InkML) en formats numériques. 🤖💡 Il intègre des techniques de vision par ordinateur et d'apprentissage profond pour un traitement complet : segmentation, classification et sélection de symboles. 📚🔍

Project files, scripts, configurations, and workflow publications for the Archives-Textract Test Project

Handwritten Bangla Character Classification using ResNet-34 trained using BanglaLekha Dataset. System has been implemented in PyTorch. For details, see the README file.

Handwritten mathematical symbols recognition with TrOCR

An android app to simplify dataset generation for digits/symbols/letters.

Line Segmentation Based on Bi-variate Gauss Statistic and Distance Metric; and Handwritten Recognition

Visualizing fully connected neural networks

Handwritten character recognition (HCR) is a challenging task due to the variability of human handwriting. This repository contains a convolutional neural network (CNN) architecture for HCR that uses Keras as an interface for the TensorFlow library. The model has been validated for English and Devanagari scripts.

Recognize hand-drawn letters in the air using a kinetic sensor.

AlexNet Model Testing In A Vast Dataset for Kurdish Digits and Isolated Characters Recognition

kanji handwriting input on android with TensorFlow Lite