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Cross-learning in analytic word recognition without segmentation

C. Choisy, A. Belaïd
2002 International Journal on Document Analysis and Recognition  
In this paper a method for analytic handwritten word recognition based on causal Markov random fields is described.  ...  First experiments on two real databases of French check amount words give very encouraging results up to 86% for recognition without rejection.  ...  Experiments on the SRTP database The database was approximately split in 66% (4627 words) for cross-learning and 34% (2404 words) for recognition tests.  ... 
doi:10.1007/s100320200078 fatcat:3ojsxzjfbzd5xckt4aldm43h4a

Unconstrained online handwritten Uyghur word recognition based on recurrent neural networks and connectionist temporal classification

Mayire Ibrayim, Wujiahematiti Simayi, Askar Hamdulla
2021 International Journal of Biometrics (IJBM)  
The traced pen-tip trajectory is fed to network without conducting segmentation and feature extraction.  ...  Recognition results are evaluated by calculating the Levenshtein-edit distance and 14.73% character error rate CER on test set of 3,600 samples for 900 word classes has been observed without help of any  ...  The second author is grateful to National Laboratory of Pattern Recognition of CASIA (Institute of Automation, Chinese Academy of Sciences) for providing the excellent study and experiment environment.  ... 
doi:10.1504/ijbm.2021.112216 fatcat:js2wjem7hzes3bqugxjf6qinfe

A Deep Learning Approach for Handwritten Arabic Names Recognition

Mohamed Elhafiz Mustafa, Murtada Khalafallah
2020 International Journal of Advanced Computer Science and Applications  
A holistic recognizer that recognizes common words directly (without segmentation) seems the plausible model for recognizing Arabic common words.  ...  Therefore, traditionally Arabic recognition systems segment a word to characters first before recognizing its characters.  ...  However, publication on word recognition are few with low recognition accuracy rate [15] , [16] . This low rate for word recognition accuracy is mainly due to the error in segmentation [1] .  ... 
doi:10.14569/ijacsa.2020.0110183 fatcat:awvvuo4u3fe4zknbope5zp2q3a

The AddressScript™ Recognition System for Handwritten Envelopes [chapter]

Alexander Filatov, Vadim Nikitin, Alexander Volgunin, Pavel Zelinsky
1999 Lecture Notes in Computer Science  
This paper presents AddressScript -a system for handwritten postal address recognition for US mail.  ...  Key aspects of AddressScript technology, such as system control flow, cursive handwriting recognition, and postal database are described.  ...  Analytical Word Recognizer The Analytical Word Recognizer is primarily intended for the recognition of numbers and hand-printed words. AWR has two stages: segmentation and recognition.  ... 
doi:10.1007/3-540-48172-9_14 fatcat:tmv2bxu4ujcrhgiupvh6zldoq4

New Segmentation Method for Analytical Recognition of Arabic Handwriting Using a Neural-Markovian Method

Khaoula Fergani, Abdelhak Bennia
2018 International Journal of Engineering and Technologies  
A new hybrid system of off-line analytical recognition of Arabic handwriting combining a neural network type multi-layer perceptron (MLP) and hidden Markov models (HMM) is presented.  ...  This description is based on statistical and structural characteristics extraction of the significant character of the handwritten Arabic words, which can be used in the MLP classification module to estimate  ...  Benouareth and Sellami [32] presented a reference system for the recognition of cursive writing off-line based on hidden Markov models, and analytical type without segmentation.  ... 
doi:10.18052/www.scipress.com/ijet.14.14 fatcat:sw6klcfc5ncrrghnxfsnu5yqvy

Urdu Nasta'liq text recognition using implicit segmentation based on multi-dimensional long short term memory neural networks

Saeeda Naz, Arif Iqbal Umar, Riaz Ahmed, Muhammad Imran Razzak, Sheikh Faisal Rashid, Faisal Shafait
2016 SpringerPlus  
Nasta'liq writing style inherits complex calligraphic nature, which presents major issues to recognition of Urdu text owing to diagonality in writing, high cursiveness, context sensitivity and overlapping  ...  We present Multi-dimensional Long Short Term Memory (MDLSTM) Recurrent Neural Networks with an output layer designed for sequence labeling for recognition of printed Urdu text-lines written in the Nasta'liq  ...  In this way, the shape of the ligature or sub-word is learned by the model without segmenting it into sub units.  ... 
doi:10.1186/s40064-016-3442-4 pmid:27942426 pmcid:PMC5122597 fatcat:toc3j66ukzhwhdgvuzrdzvlxq4

Learning to Count Words in Fluent Speech enables Online Speech Recognition [article]

George Sterpu, Christian Saam, Naomi Harte
2020 arXiv   pre-print
In this work we introduce Taris, a Transformer-based online speech recognition system aided by an auxiliary task of incremental word counting.  ...  Sequence to Sequence models, in particular the Transformer, achieve state of the art results in Automatic Speech Recognition.  ...  Since we do not explicitly model the pauses between words, and the convergence towards the segmental behaviour is a mathematical conjecture without analytic proof for now, it is likely to observe deviations  ... 
arXiv:2006.04928v3 fatcat:7nfd3jghvbehzciyeb34i7hnoy

Robust Handwriting Recognition with Limited and Noisy Data [article]

Hai Pham, Amrith Setlur, Saket Dingliwal, Tzu-Hsiang Lin, Barnabas Poczos, Kang Huang, Zhuo Li, Jae Lim, Collin McCormack, Tam Vu
2020 arXiv   pre-print
Despite the advent of deep learning in computer vision, the general handwriting recognition problem is far from solved.  ...  We break the problem into two consecutive stages of word segmentation and word recognition respectively and utilize data augmentation techniques to train both stages.  ...  Pattern Recognition, complex learning tasks. Journal of Learning Analytics, 3(2):220–238, 90:109–118, 2019. 2016.  ... 
arXiv:2008.08148v1 fatcat:4uu2d5ncsjduvjwo2ejfuikb2y

POISE: Efficient Cross-Domain Chinese Named Entity Recognization via Transfer Learning

Jiabao Sheng, Aishan Wumaier, Zhe Li
2020 Symmetry  
In addition, we also use the method of combining characters and words to reduce the problem of word segmentation across domains and reduce the error rate in label mapping.  ...  To improve the performance of deep learning methods in case of a lack of labeled data for entity annotation in entity recognition tasks, this study proposes transfer learning schemes that combine the character  ...  and words, which can reduce the problem of unclear boundaries in cross-domain word segmentation in Chinese.  ... 
doi:10.3390/sym12101673 fatcat:jwce5lmbvraibc5kxbmbxnek5i

The early stages of reading: A longitudinal study

Nick Ellis, Barbara Large
1988 Applied Cognitive Psychology  
It then changes in character, being associated with holistic visual pattern recognition skills.  ...  By 7 years old the better readers' skills are associated with analytic visual perceptual analysis, the learning of new symbol-sound associations, and sound blending skill.  ...  or word segments.  ... 
doi:10.1002/acp.2350020106 fatcat:sigzn7hozbg5bn26pf3xmsdb2a

Hybrid modelling of an off line Arabic handwriting recognition system: results and evaluation

Ons Meddeb, Mohsen Maraoui, Shadi Aljawarneh
2017 International Journal of Intelligent Enterprise  
Then, we detailed the general architecture of an Arabic Handwriting Recognition System (AHRS) and the contributions that we have proposed at each phase: first, an analytical segmentation approach based  ...  In this paper, we presented a state of the art in the field of Arabic handwriting recognition as well as the techniques used.  ...  at the level of learning and recognition.  ... 
doi:10.1504/ijie.2017.087017 fatcat:7zr4mleztveptchlm7jqnu5bca

A joint model of word segmentation and meaning acquisition through cross-situational learning

Okko Räsänen, Heikki Rasilo
2015 Psychological review  
Among researchers, a widely studied learning mechanism is called cross-situational learning (XSL).  ...  Results from simulations show that the model is not only capable of replicating behavioral data on word learning in artificial languages, but also shows effective learning of word segments and their meanings  ...  Statistical learning, word segmentation and cross-situational learning 2.1 Statistical word segmentation Statistical learning refers to the finding that infants and adults are sensitive to statistical  ... 
doi:10.1037/a0039702 pmid:26437151 fatcat:ddwfkegxrzbfja2h56xz352cyy

A Review of Arabic Optical Character Recognition Techniques & Performance
English

Yazan M Alwaqfi, Mumtazimah Mohamad
2020 International Journal of Engineering Trends and Technoloy  
In addition, the review of deep learning for Arabic OCR systems and researches is very important and useful.  ...  some cases about 99%, while using deep learning in Arabic OCR can results up to 100% accuracy with short time and less resources to process the image.  ...  without spaces in the same word, and their shape is changed in dependence of characters position in the words [4] .  ... 
doi:10.14445/22315381/cati1p208 fatcat:ilgf3ea7pfa45e2uo7iv7dszxe

Chinese text-line detection from web videos with fully convolutional networks

Chun Yang, Wei-Yi Pei, Long-Huang Wu, Xu-Cheng Yin
2018 Big Data Analytics  
Conclusion: The proposed system can directly detect the English word and Chinese characters in the caption text-lines without word or character segmentation with the high performance on real-world web  ...  Video text extraction and recognition plays an essential role in web multimedia understanding and retrieval for big visual data analytics and applications.  ...  This method can directly detect the English word and Chinese characters in the caption text-lines without word or character segmentation.  ... 
doi:10.1186/s41044-017-0028-2 fatcat:kvpm2nl2hzawlmcxciot3ha23u

Emotion Analysis Method of Teaching Evaluation Texts Based on Deep Learning in Big Data Environment

Liqin Li, Arpit Bhardwaj
2022 Computational Intelligence and Neuroscience  
In order to improve the precision and accuracy of emotion analysis, this paper proposes an emotion recognition and analysis method based on deep learning model.  ...  , and further ensure the accuracy of emotion recognition of teaching evaluation texts.  ...  Excessive word segmentation: word segmentation is too detailed, which usually appears in four-word words. is word is a complete emotional word in teaching evaluation, but the word segmentation system divides  ... 
doi:10.1155/2022/9909209 fatcat:pj3ainjaf5gotfzsc6qagodxyu
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