There are 2 repositories under handwritten-character-recognition topic.
Lightweight CRNN for OCR (including handwritten text) with depthwise separable convolutions and spatial transformer module [keras+tf]
The goal of this project is to solve the task of name transcription from handwriting images implementing a NN approach.
Handwritten Kazakh and Russian (HKR) database for text recognition
Handwritten Telugu Character Recognition using Convolutional Neural Networks
kanji handwriting input on android with TensorFlow Lite
Line Segmentation Based on Bi-variate Gauss Statistic and Distance Metric; and Handwritten Recognition
Evaluation of different machine learning models on the task of online handwritten character recognition
Zilla-64: A Bangla Handwritten Word Dataset Of 64 Districts Name of Bangladesh and Recognition Using Holistic Approach
Process Caltech Archives' digital documents and photos, and annotate each page or image with information about its contents
Handwritten mathematical symbols recognition with TrOCR
Virtual Pen + Recognition of handwritten digits
A web app to convert handwritten forms to digital forms. Initially you are supposed to upload a template of your form that isn't filled. If the templates of your form is already available, you just need to upload your handwritten form and it will be converted to digital text.
An android application which extracts handwritten text from an image.
Gujarati Handwritten Character Recognition Project.
Handwritten Character Recognition. EMNIST dataset on Kaggle. Tensorflow2 - Keras - CNN - 0.85 evaluation.
Recognize the handwritten digits online with FCNet which is powered by MNIST dataset 😄
handwritten text recognition with mxnet and gluon. Thanks to https://pythonawesome.com/handwritten-text-recognition-ocr-with-mxnet-gluon/
Handwritten text recognition using CNN with EMNIST dataset
This project aims at getting polynomial equation present in the image
HMBD: Arabic Handwritten Characters Dataset
MNIST like dataset creation tool for Handwritten Text Recognition.
Dataset of birth dates from Danish parish records
Collect handwritten characters for classification.
A convolutional neural network (CNN, or ConvNet) is a class of deep neural networks, most commonly applied to analyzing visual imagery. They are also known as shift invariant or space invariant artificial neural networks (SIANN), based on their shared-weights architecture and translation invariance characteristics. They have applications in image and video recognition, recommender systems, image classification, medical image analysis, natural language processing, brain-computer interfaces, and financial time series.
An application to classify handwritten Bengali graphemes.
In this paper, we introduce an Autoencoder with a Deep CNN, which we call DConvAENNet for recognizing Bangla Handwritten Character (BHC). A total of 22 experiments were performed on the three-character datasets (BanglaLekha-Isolated, CMATERdb 3.1, Ekush).
Fundamentals of Machine Learning (EEL5840) final project.
Preprocessing methods to enhance Tesseract-OCR in the case of printed text on difficult background, or handwritten text on lined/squared paper.
Handwritten Urdu Character Recognition in Machine Learning using Scikit-learn