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A residual-attention offline handwritten Chinese text recognition based on fully convolutional neural networks

Yintong Wang, Yingjie Yang, Weiping Ding, Shuo Li
2021 IEEE Access  
In this paper, we propose a residual-attention offline handwritten Chinese text recognition based on fully convolutional neural networks, which is segmentation-free handwritten recognition that avoids  ...  Experiments on the CASIA-HWDB and ICDAR-2013 competition dataset show that our method achieves a competitive performance on offline handwritten Chinese text recognition.  ...  FIGURE 1 . 1 The flow chart of residual-attention offline handwritten Chinese text recognition. FIGURE 2 . 2 The detailed structure of the i -th GateBlock.  ... 
doi:10.1109/access.2021.3115606 fatcat:qxjcgmlpl5amrfmewfb6fyzipa

Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR) [article]

Jamshed Memon, Maira Sami, Rizwan Ahmed Khan
2020 arXiv   pre-print
Given the ubiquity of handwritten documents in human transactions, Optical Character Recognition (OCR) of documents have invaluable practical worth.  ...  During last decade, researchers have used artificial intelligence / machine learning tools to automatically analyze handwritten and printed documents in order to convert them into electronic format.  ...  In research studies of OCR, structural models can be further sub-divided on the basis of context of structure i.e. graphical methods and grammar based methods .  ... 
arXiv:2001.00139v1 fatcat:p3rdutz35besxfxf7suozt7r2u

Sentence-level Online Handwritten Chinese Character Recognition [article]

Yunxin Li, Qian Yang, Qingcai Chen, Lin Ma, Baotian Hu, Xiaolong Wang, Yuxin Ding
2021 arXiv   pre-print
Single online handwritten Chinese character recognition~(single OLHCCR) has achieved prominent performance.  ...  The in-depth empirical analysis and case studies indicate that DSTFN can significantly improve the efficiency of handwriting input, with the handwritten Chinese character with incomplete strokes being  ...  With the advent of statistical learning methods, most of handwritten Chinese character recognition are mainly divided into structural methods and statistical methods [18, 43] , and the above two methods  ... 
arXiv:2108.02561v1 fatcat:pocccqgg6rf7to7ddwcijiibnu

A Survey on Methods for Basic Unit Segmentation in Off-line Handwritten Text Recognition

Aysadet Abliz, Wujiahemaiti Simayi, Kamil Moydin, Askar Hamdulla
2016 International Journal of Future Generation Communication and Networking  
Also, considering the very much relations between Arabic and Uyghur which we are aiming to get progress on its handwritten recognition technology, references from Arabic handwritten recognition are very  ...  Studies on recognizing different kind of handwritten texts have been conducted and achieved great success for some letters.  ...  In order to find better solutions for the problems which encountered in Uyghur handwritten text recognition, we reference some papers from English and Arabic handwritten text recognition, firstly.  ... 
doi:10.14257/ijfgcn.2016.9.11.13 fatcat:auxz4zldijendkvqscv34rqtvu

A Deep Learning Technology based OCR Framework for Recognition Handwritten Expression and Text

Tuanji Gong, Xuanxia Yao
2021 Converter  
However it still faces many challenging problems in handwritten text recognition and mathematical expression recognition, such as handwritten Chinese recognition, mixture of printed and handwritten Chinese  ...  In this paper, we introduce a deep learning based framework to detect and recognize handwritten and printed text or math expression. The framework consists of three components.  ...  Conclusion In this work, we propose a multiple-stage deep learning based framework to detect and recognize printed and handwritten text or math expression.  ... 
doi:10.17762/converter.259 fatcat:4j6jbjanvjd5ne5c32me5nfm2e

Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR)

Jamshed Memon, Maira Sami, Rizwan Ahmed Khan, Mueen Uddin
2020 IEEE Access  
Given the ubiquity of handwritten documents in human transactions, Optical Character Recognition (OCR) of documents have invaluable practical worth.  ...  During last decade, researchers have used artificial intelligence / machine learning tools to automatically analyze handwritten and printed documents in order to convert them into electronic format.  ...  [164] proposed a new neural network structure for Chinese handwritten character recognition.  ... 
doi:10.1109/access.2020.3012542 fatcat:f5bfni5kbfhf3i63lvv3t6pena

A Complete Off-line Sindhi Handwritten Text Recognition: A Survey

Shafique A. Awan, Dil Nawaz Hakro, Intzar Lashari, Akhtar H. Jalbani, Maryam Hameed
2017 Zenodo  
An integrated handwritten system will be the output of this system in which handwritten text is recognized and editable text will be available for the further processing.  ...  Intelligent Characters Recognition (ICR) is an active field in which handwritten characters are converted into editable text from the image, and remain the point of interest for researchers around the  ...  Arabic ICR using Structural and Syntactic Pattern Attributes: Parvez and Mahmoud proposed an Arabic handwritten recognition system based on structural and syntactic pattern attributes.  ... 
doi:10.5281/zenodo.3469359 fatcat:qjsiedfhd5ghtd3xnrnbz7rpla

Evaluation of Handwritten Urdu Text by Integration of MNIST Dataset Learning Experience

Saad Bin Ahmed, Ibrahim A. Hameed, Saeeda Naz, Muhammad Imran Razzak, Rubiyah Yusof
2019 IEEE Access  
This paper presents a novel way to exploit the transfer learning experience of similar patterns on handwritten Urdu text analysis.  ...  The MNIST pre-trained network is employed by transferring it's learning experience on Urdu Nastaliq Handwritten Dataset (UNHD) samples.  ...  FIGURE 4 . 4 Transfer learning based cursive handwritten text recognition. FIGURE 5 . 5 MNIST convolutional matrix with UNHD database images.  ... 
doi:10.1109/access.2019.2946313 fatcat:tbt5kml3uvhnrdkifpktxt5lya

On Study of the Reliable Fully Convolutional Networks with Tree Arranged Outputs (TAO-FCN) for Handwritten String Recognition [article]

Song Wang, Jun Sun, Satoshi Naoi
2017 arXiv   pre-print
In this paper, based on TAO-FCN, we proposed an end-to-end system for handwritten string recognition.  ...  The handwritten string recognition is still a challengeable task, though the powerful deep learning tools were introduced.  ...  Second, a path search process of beam search is conducted based on the recognition results of the TAO-FCN. Finally, the recognition of the handwritten string is obtained.  ... 
arXiv:1707.02975v1 fatcat:oborux55znft3je65n6dopxm5e

End-to-end Handwritten Chinese Paragraph Text Recognition Using Residual Attention Networks

Yintong Wang, Yingjie Yang, Haiyan Chen, Hao Zheng, Heyou Chang
2022 Intelligent Automation and Soft Computing  
To deal with these challenges, an end-to-end residual attention handwritten Chinese paragraph text recognition method is proposed, which uses fully convolutional neural networks as the main structure of  ...  Handwritten Chinese recognition which involves variant writing style, thousands of character categories and monotonous data mark process is a longterm focus in the field of pattern recognition research  ...  End-to-end handwritten Chinese text line recognition methods [8, 31] are proposed.  ... 
doi:10.32604/iasc.2022.027146 fatcat:57s5jf4apvhmzchhnc6jg24g4e

Studies of Radical Model for Retrieval of Cursive Chinese Handwritten Annotations [chapter]

Matthew Ma, Chi Zhang, Patrick Wang
2000 Lecture Notes in Computer Science  
By means of semantic matching, a handwritten annotation may also be retrieved independently of writers via typed text query, or stored texts can be retrieved by handwritten queries.  ...  Our research focuses on Chinese online ink matching that tries to match handwritten annotations with handwritten queries without attempting to recognize them.  ...  By extending Wang's Learning by Knowledge paradigm [8] , this method focuses on the semantic approach that a human learns and recognizes things and realizes such approach in the matching of Chinese handwritten  ... 
doi:10.1007/3-540-44522-6_42 fatcat:yazrwvmkqbh27eravr6lft3g3i

Editorial for special issue on "Advanced Topics in Document Analysis and Recognition"

Cheng-Lin Liu, Andreas Dengel, Rafael Dueire Lins
2019 International Journal on Document Analysis and Recognition  
In "Handwritten Arabic Text Recognition Using Multi-Stage Sub-Core Shape HMMs," Irfan Ahmad and Gernot Fink present a multi-stage HMM-based text recognition system for handwritten Arabic.  ...  First, a deep learning pipeline is proposed for detecting handwritten text, formulae and sketches and binarizing the extracted content in video frames.  ... 
doi:10.1007/s10032-019-00342-z fatcat:t4f7ruobrbf47hvudczsrg4r2q

Recurrent neural network transducer for Japanese and Chinese offline handwritten text recognition [article]

Trung Tan Ngo, Hung Tuan Nguyen, Nam Tuan Ly, Masaki Nakagawa
2021 arXiv   pre-print
In this paper, we propose an RNN-Transducer model for recognizing Japanese and Chinese offline handwritten text line images.  ...  As far as we know, it is the first approach that adopts the RNN-Transducer model for offline handwritten text recognition.  ...  In recent years, based on deep learning techniques, many segmentation-free methods are designed to surpass the problem and proven to be state-of-the-art for many text recognition datasets.  ... 
arXiv:2106.14459v1 fatcat:xg2xfoohyrbrfdcwzcinqh46hm

Segmentation-free handwritten Chinese text recognition with LSTM-RNN

Ronaldo Messina, Jerome Louradour
2015 2015 13th International Conference on Document Analysis and Recognition (ICDAR)  
Our results on the data from the Task 4 in ICDAR 2013 competition for handwritten Chinese recognition are comparable in performance with the best reported systems.  ...  We present initial results on the use of Multi-Dimensional Long-Short Term Memory Recurrent Neural Networks (MDLSTM-RNN) in recognizing lines of handwritten Chinese text without explicit segmentation of  ...  CONCLUSION We presented a handwritten text recognition system for Chinese characters based on MDLSTM-RNN, that works without segmentation the line in terms of characters.  ... 
doi:10.1109/icdar.2015.7333746 dblp:conf/icdar/MessinaL15 fatcat:6tjwzn5errar7opg5h4ns26q4m

Recognition of Automated Hand-written Digits on Document Images Making Use of Machine Learning Techniques

Hiral Raja, Aarti Gupta, Rohit Miri
2021 European Journal of Engineering and Technology Research  
Following complete segmentation, complete recognition of handwritten digits is accomplished. To assess the methods' results, data must be used for machine learning training.  ...  Deep learning methods organize the pictures by moving a fixed-size monitor over them while categorizing each sub-image as a digit pass or fail.  ...  We used pattern recognition to conduct off-line Chinese handwritten character recognition in this paper [32] , [33] titled "Post-processing for off-line Chinese handwritten character string recognition  ... 
doi:10.24018/ejers.2021.6.4.2460 fatcat:z3bn5sxpcjgnhgj2qdu7xdgcpm
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