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OCR material

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bear_fish
发布2018-09-19 12:41:52
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发布2018-09-19 12:41:52
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Papers

End-to-End Text Recognition with Convolutional Neural Networks

Word Spotting and Recognition with Embedded Attributes

Reading Text in the Wild with Convolutional Neural Networks

Deep structured output learning for unconstrained text recognition

  • intro: “propose an architecture consisting of a character sequence CNN and an N-gram encoding CNN which act on an input image in parallel and whose outputs are utilized along with a CRF model to recognize the text content present within the image.”
  • arxiv: http://arxiv.org/abs/1412.5903

Deep Features for Text Spotting

Reading Scene Text in Deep Convolutional Sequences

DeepFont

DeepFont: Identify Your Font from An Image

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

Recursive Recurrent Nets with Attention Modeling for OCR in the Wild

Writer-independent Feature Learning for Offline Signature Verification using Deep Convolutional Neural Networks

DeepText

DeepText: A Unified Framework for Text Proposal Generation and Text Detection in Natural Images

End-to-End Interpretation of the French Street Name Signs Dataset

End-to-End Subtitle Detection and Recognition for Videos in East Asian Languages via CNN Ensemble with Near-Human-Level Performance

Smart Library: Identifying Books in a Library using Richly Supervised Deep Scene Text Reading

Text Detection

Object Proposals for Text Extraction in the Wild

Text-Attentional Convolutional Neural Networks for Scene Text Detection

Accurate Text Localization in Natural Image with Cascaded Convolutional Text Network

Synthetic Data for Text Localisation in Natural Images

Scene Text Detection via Holistic, Multi-Channel Prediction

Detecting Text in Natural Image with Connectionist Text Proposal Network

TextBoxes: A Fast Text Detector with a Single Deep Neural Network

Text Recognition

Sequence to sequence learning for unconstrained scene text recognition

Drawing and Recognizing Chinese Characters with Recurrent Neural Network

Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition

Stroke Sequence-Dependent Deep Convolutional Neural Network for Online Handwritten Chinese Character Recognition

Breaking Captcha

Using deep learning to break a Captcha system

Breaking reddit captcha with 96% accuracy

I’m not a human: Breaking the Google reCAPTCHA

Neural Net CAPTCHA Cracker

Recurrent neural networks for decoding CAPTCHAS

Reading irctc captchas with 95% accuracy using deep learning

端到端的OCR:基于CNN的实现

I Am Robot: (Deep) Learning to Break Semantic Image CAPTCHAs

Handwritten Recognition

High Performance Offline Handwritten Chinese Character Recognition Using GoogLeNet and Directional Feature Maps

Recognize your handwritten numbers

https://medium.com/@o.kroeger/recognize-your-handwritten-numbers-3f007cbe46ff#.jllz62xgu

Handwritten Digit Recognition using Convolutional Neural Networks in Python with Keras

MNIST Handwritten Digit Classifier

如何用卷积神经网络CNN识别手写数字集?

LeNet – Convolutional Neural Network in Python

Scan, Attend and Read: End-to-End Handwritten Paragraph Recognition with MDLSTM Attention

MLPaint: the Real-Time Handwritten Digit Recognizer

Training a Computer to Recognize Your Handwriting

https://medium.com/@annalyzin/training-a-computer-to-recognize-your-handwriting-24b808fb584#.gd4pb9jk2

Using TensorFlow to create your own handwriting recognition engine

Building a Deep Handwritten Digits Classifier using Microsoft Cognitive Toolkit

Plate Recognition

Reading Car License Plates Using Deep Convolutional Neural Networks and LSTMs

Number plate recognition with Tensorflow

end-to-end-for-plate-recognition

Blogs

Applying OCR Technology for Receipt Recognition

Hacking MNIST in 30 lines of Python

Projects

ocropy: Python-based tools for document analysis and OCR

Extracting text from an image using Ocropus

CLSTM : A small C++ implementation of LSTM networks, focused on OCR

caffe-ocr: OCR with caffe deep learning framework

Digit Recognition via CNN: digital meter numbers detection

Attention-OCR: Visual Attention based OCR

umaru: An OCR-system based on torch using the technique of LSTM/GRU-RNN, CTC and referred to the works of rnnlib and clstm

Tesseract.js: Pure Javascript OCR for 62 Languages

DeepHCCR: Offline Handwritten Chinese Character Recognition based on GoogLeNet and AlexNet (With CaffeModel)

Datasets

COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images

Videos

LSTMs for OCR

Resources

Scene Text Localization & Recognition Resources

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目录
  • Papers
    • DeepFont
      • DeepText
      • Text Detection
      • Text Recognition
      • Breaking Captcha
      • Handwritten Recognition
      • Plate Recognition
      • Blogs
      • Projects
      • Datasets
      • Videos
      • Resources
      相关产品与服务
      AI 应用产品
      文字识别(Optical Character Recognition,OCR)基于腾讯优图实验室的深度学习技术,将图片上的文字内容,智能识别成为可编辑的文本。OCR 支持身份证、名片等卡证类和票据类的印刷体识别,也支持运单等手写体识别,支持提供定制化服务,可以有效地代替人工录入信息。
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