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Multi-level Modeling of Manuscripts for Authorship Identification with Collective Decision Systems [chapter]

Salvador Godoy-Calderón, Edgardo M. Felipe-Riverón, Edith C. Herrera-Luna
2012 Lecture Notes in Computer Science  
In the context of forensic and criminalistics studies the problem of identifying the author of a manuscript is generally expressed as a supervisedclassification problem.  ...  In this paper a new approach for modeling a manuscript at the word and text line levels is presented.  ...  The authors would like to thank the Academic Secretary, COFAA, Postgraduate and Research Secretary, and Centre for Computing Research of the National Polytechnic Institute (IPN), CONACyT and SNI, for their  ... 
doi:10.1007/978-3-642-33275-3_93 fatcat:ql5xdy3b5nabbitnzflc7khipi

A Sequential Handwriting Recognition Model Based on a Dynamically Configurable CRNN

Ahmed AL-Saffar, Suryanti Awang, Wafaa AL-Saiagh, Ahmed Salih AL-Khaleefa, Saad Adnan Abed
2021 Sensors  
Because most applications of handwriting recognition in real life contain sequential text in various languages, there is a need to develop a dynamic handwriting recognition system.  ...  The proposed DC-CRNN is based on the Salp Swarm Optimization Algorithm (SSA), which generates the optimal structure and hyperparameters for Convolutional Recurrent Neural Networks (CRNNs).  ...  Accurate recognition of handwritten text has remained a prime problem of interest for many decades.  ... 
doi:10.3390/s21217306 pmid:34770612 pmcid:PMC8587523 fatcat:o2umjghgcvccrb7g3tonz4nf34

Devanagari ancient documents recognition using statistical feature extraction techniques

Sonika Narang, M K Jindal, Munish Kumar
2019 Sadhana (Bangalore)  
Authors have achieved 88.95% recognition accuracy using a combination of all features and a combination of all classifiers considered in this work by a simple majority voting scheme. adhana(0123456789(  ...  A data set, of 6152 pre-segmented samples of Devanagari ancient documents, is considered for experimental work.  ...  Based on the related work, authors noticed that a lot of work has been done for printed and handwritten text recognition of different scripts.  ... 
doi:10.1007/s12046-019-1126-9 fatcat:e4uzem3tszhm3hjfgcghdf2p44

Recognizing Ancient Characters from Tamil Palm Leaf Manuscripts using Convolution Based Deep Learning

2019 International journal of recent technology and engineering  
The outputs reveal that the proposed approach generates better rates of recognition than that of schemes based on feature extraction for handwritten character recognition.  ...  Generally Optical character recognition is the method of e-translation of typewritten text or handwritten images into machine editable text.  ...  A convolutional neural network is a specific kind of ANN that employs perceptron ML algorithm for supervised learning to examine the data.  ... 
doi:10.35940/ijrte.c5842.098319 fatcat:eg77ppqtczaodphbxnhoinypqi

Text feature extraction based on deep learning: a review

Hong Liang, Xiao Sun, Yunlei Sun, Yuan Gao
2017 EURASIP Journal on Wireless Communications and Networking  
Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features.  ...  As a new feature extraction method, deep learning has made achievements in text mining.  ...  Competing interests The authors declare that they have no competing interests.  ... 
doi:10.1186/s13638-017-0993-1 pmid:29263717 pmcid:PMC5732309 fatcat:bqyk3wddqbebdfeki72myn5p2y

A Review of Arabic Optical Character Recognition Techniques & Performance

Yazan M Alwaqfi, Mumtazimah Mohamad
2020 International Journal of Engineering Trends and Technoloy  
Several studies focused the interest in Optical Character Recognition, which is computer software designed for converting images with text into machine processed text.  ...  This paper presents a literature review on the existing systems Arabic text recognition, consists of a typical mechanism, lists the differences, advantages, and disadvantages that help in adopting or expanding  ...  ACKNOWLEDGEMENT This work is supported by UniSZA Center of Excellence Management and Research Incubator and University Sultan Zainal Abidin, Terengganu, Malaysia.  ... 
doi:10.14445/22315381/cati1p208 fatcat:ilgf3ea7pfa45e2uo7iv7dszxe

SLOGAN: Handwriting Style Synthesis for Arbitrary-Length and Out-of-Vocabulary Text [article]

Canjie Luo, Yuanzhi Zhu, Lianwen Jin, Zhe Li, Dezhi Peng
2022 arXiv   pre-print
Large amounts of labeled data are urgently required for the training of robust text recognizers.  ...  Our method can synthesize words that are not included in the training vocabulary and with various new styles.  ...  Algorithm 1 : 1 Training scheme. The overall differentiable framework can back-propagate the gradients to update the style latent vector z z z in the style bank.  ... 
arXiv:2202.11456v1 fatcat:c6vpdg2v4rge5iymjfnk3rfyb4

A Review of Machine Learning Algorithms for Text-Documents Classification

Baharum Baharudin, Lam Hong Lee, Khairullah Khan
2010 Journal of Advances in Information Technology  
With the increasing availability of electronic documents and the rapid growth of the World Wide Web, the task of automatic categorization of documents became the key method for organizing the information  ...  This paper provides a review of the theory and methods of document classification and text mining, focusing on the existing literature.  ...  Also in [19] the authors introduced a new weighting method based on statistical estimation of the importance of a word categorization problem.  ... 
doi:10.4304/jait.1.1.4-20 fatcat:nx23oqf3gbgiha45s2enn2hqqq

Continuous Offline Handwriting Recognition using Deep Learning Models [article]

Jorge Sueiras
2021 arXiv   pre-print
This Thesis addresses the offline continuous handwritten text recognition (HTR) problem, consisting of developing algorithms and models capable of transcribing the text present in an image without the  ...  The new proposed model provides competitive results with those obtained with other well-established methodologies.  ...  Having a deep understanding of how this problem has been proposed to be solved allows making the best decisions to address it with a new approach. • Explore new normalization algorithms of handwritten  ... 
arXiv:2112.13328v1 fatcat:xkcdw7c2rngd7jsaixsfosqzc4

Survey on Segmentation and Recognition of Handwritten Arabic Script

Amani Ali Ahmed Ali, M. Suresha
2020 SN Computer Science  
This paper presents various algorithms with respect to text, word and characters segmentation and recognition of Arabic document.  ...  Most of the previous published works have been analyzed, and some remedies have been suggested. Various strategies used for creating a powerful recognition system have been summarized.  ...  A new algorithm for automatic segmentation of text line in Arabic handwritten documents has been introduced in Boussellaa et al. [22] .  ... 
doi:10.1007/s42979-020-00187-y fatcat:qows2arqnngzbpo5p63aoecjjm

Arabic Handwriting Recognition Model based on Neural Network Approach

Abdullah Manal
2019 International Journal of Advanced Trends in Computer Science and Engineering  
The recognition rate of the proposed model is 70%. This result showed how much the proper selection of the preprocessing steps affects the recognition rate of handwritten words.  ...  The propo sed model differs from other suggested models in Arabic handwriting field, according, the unlike preprocessing steps applied on a model and a new approach in estimating and correcting words baseline  ...  The advantage of this approach is the ability to identify characters via abstraction which is wonderful for faxed files and harmed text.  ... 
doi:10.30534/ijatcse/2019/4581.120419 fatcat:3jkyrz4bafbenb3jkoe6u7wdxy

A Survey on Resilient Machine Learning [article]

Atul Kumar, Sameep Mehta
2017 arXiv   pre-print
Maliciously created input samples can affect the learning process of a ML system by either slowing down the learning process, or affecting the performance of the learned mode, or causing the system make  ...  We present a survey of this emerging area in machine learning.  ...  Semi-Supervised Text Classification Adversarial training is used for regularizing supervised learning algorithms and virtual adversarial training extends supervised learning algorithms to the semi-supervised  ... 
arXiv:1707.03184v1 fatcat:qjylw7bvkzbdlbrof5cfpy2jyq

SKETRACK: Stroke-Based Recognition of Online Hand-Drawn Sketches of Arrow-Connected Diagrams and Digital Logic Circuit Diagrams

Oğuz Altun, Orhan Nooruldeen
2019 Scientific Programming  
Digitalization of handwritten documents has created a greater need for accurate online recognition of hand-drawn sketches.  ...  This paper focuses on the design and development of a new, efficient stroke-based online hand-drawn sketch recognition scheme named SKETRACK for hand-drawn arrow diagrams and digital logic circuit diagrams  ...  . e lion optimization algorithm has dual purpose in the SKETRACK scheme.  ... 
doi:10.1155/2019/6501264 fatcat:chjuvsd4jrajldmuabyypg6szi

Clock Drawing Test Digit Recognition Using Static and Dynamic Features

Zainab Harbi, Yulia Hicks, Rossitza Setchi
2016 Procedia Computer Science  
In this paper, a new system for numeral handwriting recognition in the CDT is proposed.  ...  The clock drawing test (CDT) is a standard neurological test for detection of cognitive impairment.  ...  In addition, the author identified new CDT drawing features important for such classification.  ... 
doi:10.1016/j.procs.2016.08.166 fatcat:pzdtzzritvbrvajrzeps5n6sqm

AI-Assisted Authentication: State of the Art, Taxonomy and Future Roadmap [article]

Guangyi Zhu, Yasir Al-Qaraghuli
2022 arXiv   pre-print
With the emerging AI-assisted authentication schemes, our comprehensive survey provides an overall understanding on a high level, which paves the way for future research in this area.  ...  AI helps break through the limitations of traditional algorithms and provides more efficient and flexible methods for solving problems.  ...  the process and proposed a new iris authen-tication scheme with deep learning algorithm to help accurately segment and identify iris patterns  ... 
arXiv:2204.12492v1 fatcat:vdeuhy63cvawjdhclricvkq42q
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