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Printed Arabic Text Recognition using Linear and Nonlinear Regression
2017
International Journal of Advanced Computer Science and Applications
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However, due to complexity of Arabic language, recognition of printed and handwritten Arabic text remained untouched for a very long time compared with English and Chinese. ...
Although, in the last few years, significant number of researches has been done in recognizing printed and handwritten Arabic text, it stills an open research field due to cursive nature of Arabic script ...
[12] have proposed small-size printed Arabic text recognition approach based on hidden Markov (HMM) model estimation. ...
doi:10.14569/ijacsa.2017.080129
fatcat:e34ctg7ojrextdw43uqy63j4xu
Deep sparse auto-encoder features learning for Arabic text recognition
2021
IEEE Access
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INDEX TERMS Arabic text recognition, feature learning, bag of features, sparse auto-encoder, hidden Markov models. ...
We propose a novel hybrid network, combining a Bag-of-Feature (BoF) framework for feature extraction based on a deep Sparse Auto-Encoder (SAE), and Hidden Markov Models (HMMs), for sequence recognition ...
Reference [53] proposed a system for discovering a boundary model of small-size Arabic printed text recognition. ...
doi:10.1109/access.2021.3053618
fatcat:p7jhbokjsjbunceuq4lu7xnmci
Deep Learning Algorithms for Arabic Handwriting Recognition: A Review
2018
International Journal of Engineering & Technology
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We review the various current deep learning approaches and tools used for Arabic handwritten recognition (AHWR), identified challenges along this line of this research, and gives several recommendations ...
(DL) dramatically improved the state-of-the-art in visual object recognition, object detection, handwritten recognition and many other domains. ...
In the study by Rani and Lehal [17] , the author proposed a system which carried out offline recognition of the Arabic cursive handwritten texts using the Hidden Markov Models (HMMs). ...
doi:10.14419/ijet.v7i3.20.19271
fatcat:ei7vonkky5eltmvnsyo7mf72d4
Dynamic and Contextual Information in HMM Modeling for Handwritten Word Recognition
2011
IEEE Transactions on Pattern Analysis and Machine Intelligence
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For modeling the contextual units, a state-tying process based on decision tree clustering is introduced. ...
The results obtained show that contextual information embedded with dynamic modeling significantly improves recognition. ...
We use the Hidden Markov Model Toolkit (HTK [48] ) for training and recognition. ...
doi:10.1109/tpami.2011.22
pmid:21282849
fatcat:32iveud5vnd77oeqjbkfv64kci
Finding Structure in Text, Genome and Other Symbolic Sequences
[article]
2012
arXiv
pre-print
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A variety of applications for these methods are examined in detail. These applications are drawn from the area of text analysis and genetic sequence analysis. ...
Since these methods are abstract in nature, they can be applied in novel situations with relative ease. ...
The hidden Markov model is used extensively in speech recognition. Hidden Markov models are described in section 1.4. ...
arXiv:1207.1847v1
fatcat:atx6naydzjbzrcrfrbnyn4uqcu
Has Computational Linguistics Become More Applied?
[chapter]
2009
Lecture Notes in Computer Science
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This paper provides a novel model for English/Arabic Query Translation to search Arabic text, and then expands the Arabic query to handle Arabic OCR-Degraded Text. ...
The vector space model approached is modified in order to develop a more flexible clustering technique. ...
Furthermore, as a big number of books and documents are available only in print especially the Arabic ones, they are not 'full text' searchable and they need applying the Arabic OCR process whose accuracy ...
doi:10.1007/978-3-642-00382-0_1
fatcat:oddvfzds4nfwjam2ccqeaxe2y4
Automatic Language Identification in Texts: A Survey
[article]
2018
arXiv
pre-print
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Finally, we identify open issues, survey the work to date on each issue, and propose future directions for research in LI. ...
Today, LI is a key part of many text processing pipelines, as text processing techniques generally assume that the language of the input text is known. ...
Acknowledgments This research was supported in part by the Australian Research Council, the Kone Foundation and the Academy of Finland. ...
arXiv:1804.08186v2
fatcat:4rmixp4i5fb55itb7ze5avkgqy
Automatic Language Identification in Texts: A Survey
2019
The Journal of Artificial Intelligence Research
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Finally, we identify open issues, survey the work to date on each issue, and propose future directions for research in LI. ...
Language identification ("LI") is the problem of determining the natural language that a document or part thereof is written in. Automatic LI has been extensively researched for over fifty years. ...
Acknowledgments This research was supported in part by the Australian Research Council, the Kone Foundation and the Academy of Finland. ...
doi:10.1613/jair.1.11675
fatcat:axugpuogyne3nptvamgd3zwgty
New Method for Calculating Causal Relationships (At: XXIII International Biometric Conference, Montréal, Québec, Canada, page 49)
2006
Zenodo
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A new method for calculating causal relationships has been presented at this conference. ...
Schaarschmidt, University of
Hannover
T6.1 Estimating the Risk of
Secondary Transmission of vCJD: A
Hidden Markov Model Approach
M. ...
Peng, University of California
10:30 TH9.2 Exploring the State
Sequence Space for Hidden
Markov and Semi-Markov Chains
Y. ...
doi:10.5281/zenodo.3902085
fatcat:fiwpmehgwzbwnfc6ths447hk7i
Linguistic Annotation
[chapter]
2010
The Handbook of Computational Linguistics and Natural Language Processing
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Portions of this paper were presented in our course on computational models of dialogue at the 2008 ESSLLI summer school in Hamburg; we would like to thank the participants there for their feedback. ...
The work of the second author has been partially supported by a Dutch NWO Veni project (grant number 275-80-002). ...
Parsing models As is the case for simple models like naïve Bayes text classifiers and hidden Markov models for tagging, we can easily construct a MaxEnt version of probabilistic context-free grammars ( ...
doi:10.1002/9781444324044.ch10
fatcat:peq2ppl6gnfklh7gtwzbrt5xym
Getting Past the Language Gap: Innovations in Machine Translation
[chapter]
2012
Mobile Speech and Advanced Natural Language Solutions
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Alignment of phrases goes in both directions and in this case allows for optimized results -always with IBM3 model. ...
Different types of constraints are applied to alignment processes as regards for instance the maximum size of segments involved in the mapping; or the maximum distance allowed for aligned segments with ...
Acoustic model training was performed with fixed state alignments and Vocal Tract Length Normalization (VTLN) factors … The system uses left-to-right hidden Markov Models (HMM)s without state skipping ...
doi:10.1007/978-1-4614-6018-3_6
fatcat:2njkc6meabhaxosl4wircumfjm
Logarithmic opinion pools for conditional random fields
2005
Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics - ACL '05
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Most of this work has demonstrated the need, directly or indirectly, to employ some form of regularisation when applying CRFs in order to overcome the tendency for these models to overfit. ...
Within NLP itself we have seen many different application areas, like named entity recognition, shallow parsing, information extraction from research papers and language modelling. ...
Hidden Markov models have been applied to a number of labelling tasks in speech recognition (Rabiner, 1989) and natural language processing, including part-of-speech tagging (Kupiec, 1992) , information ...
doi:10.3115/1219840.1219843
dblp:conf/acl/SmithCO05
fatcat:53svuw7t3nephd5dq7os2vgzpm
Relation Extraction : A Survey
[article]
2017
arXiv
pre-print
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This extracted information can be used to improve access and management of knowledge hidden in large text corpora. ...
With the advent of the Internet, large amount of digital text is generated everyday in the form of news articles, research publications, blogs, question answering forums and social media. ...
Acknowledgement The authors would like to thank Swapnil Hingmire for his efforts of reviewing the draft and providing several useful suggestions for improvement. ...
arXiv:1712.05191v1
fatcat:aiezdqep3faltozs6gusvxoite
Proceedings of the BioCreative V.5 Challenge Evaluation Workshop
2022
Zenodo
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for funding. ...
We would like to thank Matthias Herzog for technical support and Milena Kraus for her support of mapping the semantic types.
Acknowledgments ...
As a semi-Markov model, it performs segmentation and classification simultaneously, allowing one state per entity type instead of two states (as in the BIO scheme) or four states (as in the BIOEW scheme ...
doi:10.5281/zenodo.6519885
fatcat:gzzr6ogkwvfe3eglv6anrzt5s4
Engineering, Technology & Applied Science Research (ETASR), Vol. 11, No. 3, pp. 7069-7290
2021
Zenodo
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Engineering, Technology & Applied Science Research (ETASR) is an international bimonthly wide scope, peer-reviewed open access journal for the publication of original articles concerned with diverse aspects ...
The journal was first published in February 2011. ISSN: 1792-8036 and 2241-4487. ...
We also thank the NED University of Engineering and Technology for providing us the platform to carry out this work.
ACKNOWLEDGMENT The work presented in this paper was supported by ...
doi:10.5281/zenodo.5136285
fatcat:2beknqdb3bcq7fqfav6btil6ci
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