Accurate, data-efficient, unconstrained text recognition with convolutional neural networks
Authors:
- Mohamed YousefMYMohamed Yousef
- Khaled F. HussainKHKhaled F. Hussain
- Usama S. MohammedUMUsama S. Mohammed
- 1 December 2020
- journal article
- research article
- Published by Elsevier in Pattern Recognition
- Vol. 108
Abstract
No abstract availableKeywords
All Related Versions
This publication has 13 references indexed in Scilit:
- A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAsScience, 2017
- Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text RecognitionIEEE Transactions on Pattern Analysis and Machine Intelligence, 2017
- Improving handwritten Chinese text recognition using neural network language models and convolutional neural network shape modelsPattern Recognition, 2017
- An End-to-End Trainable Neural Network for Image-Based Sequence Recognition and Its Application to Scene Text RecognitionIEEE Transactions on Pattern Analysis and Machine Intelligence, 2016
- Text Detection and Recognition in Imagery: A SurveyIEEE Transactions on Pattern Analysis and Machine Intelligence, 2014
- KHATT: An open Arabic offline handwritten text databasePattern Recognition, 2014
- Framewise phoneme classification with bidirectional LSTM and other neural network architecturesNeural Networks, 2005
- The IAM-database: an English sentence database for offline handwriting recognitionInternational Journal on Document Analysis and Recognition (IJDAR), 2002
- Long Short-Term MemoryNeural Computation, 1997
- Acceleration of Stochastic Approximation by AveragingSIAM Journal on Control and Optimization, 1992