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Printed Arabic Text Recognition using Linear and Nonlinear Regression

Ashraf A.
2017 International Journal of Advanced Computer Science and Applications  
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

Najoua Rahal, Maroua Tounsi, Amir Hussain, Adel M. Alimi
2021 IEEE Access  
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

Ahmed AL-Saffar, Suryanti Awang, Wafaa AL-Saiagh, Sabrina Tiun, A S. Al-khaleefa
2018 International Journal of Engineering & Technology  
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

A.-L Bianne-Bernard, F. Menasri, R. Al-Hajj Mohamad, C. Mokbel, C. Kermorvant, Laurence Likforman-Sulem
2011 IEEE Transactions on Pattern Analysis and Machine Intelligence  
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]

Ted Dunning
2012 arXiv   pre-print
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]

Kenneth Church
2009 Lecture Notes in Computer Science  
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]

Tommi Jauhiainen, Marco Lui, Marcos Zampieri, Timothy Baldwin, Krister Lindén
2018 arXiv   pre-print
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

Tommi Jauhiainen, Marco Lui, Marcos Zampieri, Timothy Baldwin, Krister Lindén
2019 The Journal of Artificial Intelligence Research  
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)

Ilija Barukčić
2006 Zenodo  
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]

Martha Palmer, Nianwen Xue
2010 The Handbook of Computational Linguistics and Natural Language Processing  
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]

Rodolfo Delmonte
2012 Mobile Speech and Advanced Natural Language Solutions  
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

Andrew Smith, Trevor Cohn, Miles Osborne
2005 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics - ACL '05  
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]

Sachin Pawar, Girish K. Palshikar, Pushpak Bhattacharyya
2017 arXiv   pre-print
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

Martin Krallinger, Alfonso Valencia
2022 Zenodo  
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

Various
2021 Zenodo  
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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