Handwritten Text Recognition (HTR) system implemented with TensorFlow.
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Updated
Apr 6, 2024 - Python
Handwritten Text Recognition (HTR) system implemented with TensorFlow.
Use Convolutional Recurrent Neural Network to recognize the Handwritten line text image without pre segmentation into words or characters. Use CTC loss Function to train.
OCR engine for all the languages
TensorFlow convolutional recurrent neural network (CRNN) for text recognition
Official implementation for ICDAR 2021 best poster paper "Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer"
Page to PAGE Layout Analysis Tool
Public implementation of our CVPR Paper "OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page TextRecognition by learning to unfold"
Detect and read handwritten words on scanned pages.
Lightweight CRNN for OCR (including handwritten text) with depthwise separable convolutions and spatial transformer module [keras+tf]
Ground Truth Resources for the HTR of patrimonial documents
End-to-end model training and deployment reference for handwritten Chinese text recognition, and can also be extended to other languages.
Use Convolutional Recurrent Neural Network to recognize the Handwritten Word text image without pre segmentation into words or characters. Use CTC loss Function to train.
Powerful handwritten text recognition. A simple-to-use, unofficial implementation of the paper "TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models".
Official implementation for ECCV 2022 paper "CoMER: Modeling Coverage for Transformer-based Handwritten Mathematical Expression Recognition"
Using Tensorflow to classify the NIST Dataset 19 (Handwriting)
Convert Arabic Handwritten Images to Text
(Deprecated) deep learning based Chinese handwriting character recognition, 基于深度学习的手写汉字地址识别
Apply different text recognition services to images of handwritten documents.
Tensorflow implementation of handwritten sequence of small letters recognition.
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