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Journal articles on the topic 'Online Handwritten Words'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 September 2023

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1

Singh, Sukhdeep, and Anuj Sharma. "Online Handwritten Gurmukhi Words Recognition." ACM Transactions on Asian and Low-Resource Language Information Processing 18, no. 3 (2019): 1–55. http://dx.doi.org/10.1145/3282441.

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Naik, Vishal A., and Apurva A. Desai. "Online Handwritten Gujarati Word Recognition." International Journal of Computer Vision and Image Processing 9, no. 1 (2019): 35–50. http://dx.doi.org/10.4018/ijcvip.2019010103.

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In this article, an online handwritten word recognition system for the Gujarati language is presented by combining strokes, characters, punctuation marks, and diacritics. The authors have used a support vector machine classification algorithm with a radial basis function kernel. The authors used a hybrid features set. The hybrid feature set consists of directional features with curvature data. The authors have used a normalized chain code and zoning-based chain code features. Words are a combination of characters and diacritics. Recognized strokes require post-processing to form a word. The au
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., G. Mandal, and T. Biswas. "Slant Estimation and Correction for Online Handwritten Bengali Words." International Journal of Computer Sciences and Engineering 6, no. 5 (2018): 535–39. http://dx.doi.org/10.26438/ijcse/v6i5.535539.

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Sen, Shibaprasad, Shubham Chowdhury, Mridul Mitra, Friedhelm Schwenker, Ram Sarkar, and Kaushik Roy. "A novel segmentation technique for online handwritten Bangla words." Pattern Recognition Letters 139 (November 2020): 26–33. http://dx.doi.org/10.1016/j.patrec.2018.02.008.

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Kanmani, Dr S., B. Sujitha, K. Subalakshmi, S. Umamaheswari, and Karimreddy Punya Sai Teja Reddy. "Off-Line and Online Handwritten Character Recognition Using RNN-GRU Algorithm." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (2023): 2518–26. http://dx.doi.org/10.22214/ijraset.2023.50184.

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Abstract: Recognizing handwritten characters is an extremely difficult task in the domains of pattern recognition and computer vision. It involves the use of a process that enables computers to identify and convert handwritten or printed characters, such as letters and numbers, into a digital format that is usable by the computer. Currently, the RNN-CNN hybrid algorithm is employed to predict handwritten text in images with an accuracy rate of 91.5%. However, the existing system can only recognize characters and words character-by-character and word-by-word. The proposed system aims to address
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Ghosh, Rajib, and Gouranga Mandal. "A Novel Approach of Skew Correction for Online Handwritten Words." International Journal of Computer Applications 48, no. 9 (2012): 45–48. http://dx.doi.org/10.5120/7380-0304.

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Ghosh, Rajib, and Prabhat Kumar. "SVM and HMM Classifier Combination Based Approach for Online Handwritten Indic Character Recognition." Recent Advances in Computer Science and Communications 13, no. 2 (2020): 200–214. http://dx.doi.org/10.2174/2213275912666181127124711.

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Background: The growing use of smart hand-held devices in the daily lives of the people urges for the requirement of online handwritten text recognition. Online handwritten text recognition refers to the identification of the handwritten text at the very moment it is written on a digitizing tablet using some pen-like stylus. Several techniques are available for online handwritten text recognition in English, Arabic, Latin, Chinese, Japanese, and Korean scripts. However, limited research is available for Indic scripts. Objective: This article presents a novel approach for online handwritten num
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Thein, Yadana, and San Su Su Yee. "Online Myanmar Handwritten Compound Words Recognition and Erratum Detection with MICR." International Journal of Computer Applications 9, no. 6 (2010): 17–22. http://dx.doi.org/10.5120/1390-1873.

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Sundaram, Suresh, and A. G. Ramakrishnan. "Attention-Feedback Based Robust Segmentation of Online Handwritten Isolated Tamil Words." ACM Transactions on Asian Language Information Processing 12, no. 1 (2013): 1–25. http://dx.doi.org/10.1145/2425327.2425331.

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Singh, Sukhdeep, Anuj Sharma, and Indu Chhabra. "Online Handwritten Gurmukhi Strokes Dataset Based on Minimal Set of Words." ACM Transactions on Asian and Low-Resource Language Information Processing 16, no. 1 (2016): 1–20. http://dx.doi.org/10.1145/2896318.

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Sen, Shibaprasad, Ankan Bhattacharyya, Ram Sarkar, and Kaushik Roy. "BYANJON: A Ground Truth Preparation System for Online Handwritten Bangla Documents." ACM Transactions on Asian and Low-Resource Language Information Processing 20, no. 6 (2021): 1–16. http://dx.doi.org/10.1145/3464379.

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The work reported in this article deals with the ground truth generation scheme for online handwritten Bangla documents at text-line, word, and stroke levels. The aim of the proposed scheme is twofold: firstly, to build a document level database so that future researchers can use the database to do research in this field. Secondly, the ground truth information will help other researchers to evaluate the performance of their algorithms developed for text-line extraction, word extraction, word segmentation, stroke recognition, and word recognition. The reported ground truth generation scheme sta
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Mandal, Gouranga. "An Innovative Approach of Dehooking for Online Handwritten Bengali Characters and Words." International Journal of Computer Sciences and Engineering 6, no. 1 (2018): 304–7. http://dx.doi.org/10.26438/ijcse/v6i1.304307.

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Abuzaraida, Mustafa Ali, Mohammed Elmehrek, and Esam Elsomadi. "Online handwriting Arabic recognition system using k-nearest neighbors classifier and DCT features." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 4 (2021): 3584. http://dx.doi.org/10.11591/ijece.v11i4.pp3584-3592.

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With advances in machine learning techniques, handwriting recognition systems have gained a great deal of importance. Lately, the increasing popularity of handheld computers, digital notebooks, and smartphones give the field of online handwriting recognition more interest. In this paper, we propose an enhanced method for the recognition of Arabic handwriting words using a directions-based segmentation technique and discrete cosine transform (DCT) coefficients as structural features. The main contribution of this research was combining a total of 18 structural features which were extracted by D
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Kutzner, Tobias, Carlos Pazmiño-Zapatier, Matthias Gebhard, Ingrid Bönninger, Wolf-Dietrich Plath, and Carlos Travieso. "Writer Identification Using Handwritten Cursive Texts and Single Character Words." Electronics 8, no. 4 (2019): 391. http://dx.doi.org/10.3390/electronics8040391.

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One of the biometric methods in authentication systems is the writer verification/identification using password handwriting. The main objective of this paper is to present a robust writer verification system by using cursive texts as well as block letter words. To evaluate the system, two datasets have been used. One of them is called Secure Password DB 150, which is composed of 150 users with 18 samples of single character words per user. Another dataset is public and called IAM online handwriting database, and it is composed of 220 users of cursive text samples. Each sample has been defined
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Sundaram, Suresh, and A. G. Ramakrishnan. "Bigram Language Models and Reevaluation Strategy for Improved Recognition of Online Handwritten Tamil Words." ACM Transactions on Asian and Low-Resource Language Information Processing 14, no. 2 (2015): 1–28. http://dx.doi.org/10.1145/2671014.

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Gmati, C., and H. Amiri. "A Global Online Handwriting Recognition Approach Based on Frequent Patterns." Engineering, Technology & Applied Science Research 8, no. 3 (2018): 2887–91. http://dx.doi.org/10.48084/etasr.1784.

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In this article, the handwriting signals are represented based on geometric and spatio-temporal characteristics to increase the feature vectors relevance of each object. The main goal was to extract features in the form of a numeric vector based on the extraction of frequent patterns. We used two types of frequent motifs (closed frequent patterns and maximal frequent patterns) that can represent handwritten characters pertinently. These common features patterns are generated from a raw data transformation method to achieve high relevance. A database of words consisting of two different letters
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Adeyanju, Ibrahim, Olusayo Fenwa, and Elijah Omidiora. "EFFECT OF NON-IMAGE FEATURES ON RECOGNITION OF HANDWRITTEN ALPHA-NUMERIC CHARACTERS." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 13, no. 11 (2014): 5155–61. http://dx.doi.org/10.24297/ijct.v13i11.2785.

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Handwritten character recognition has applications in several industries such as Banking for reading of cheques and Libraries/ National archives for digital searchable storage of historic texts. The main feature typically used for the recognition task is the character image. However, there are other possible features such as the hand (left or right) used by author, number of strokes and other geometric features that can be captured when writing on digital devices. This paper investigates the effect of using some non-image features on the recognition rate of three classifiers: Instance Based L
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Dinges, Laslo, Ayoub Al-Hamadi, Moftah Elzobi, Sherif El-etriby, and Ahmed Ghoneim. "ASM Based Synthesis of Handwritten Arabic Text Pages." Scientific World Journal 2015 (2015): 1–18. http://dx.doi.org/10.1155/2015/323575.

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Document analysis tasks, as text recognition, word spotting, or segmentation, are highly dependent on comprehensive and suitable databases for training and validation. However their generation is expensive in sense of labor and time. As a matter of fact, there is a lack of such databases, which complicates research and development. This is especially true for the case of Arabic handwriting recognition, that involves different preprocessing, segmentation, and recognition methods, which have individual demands on samples and ground truth. To bypass this problem, we present an efficient system th
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XU, RUIFENG, DANIEL YEUNG, WENHAO SHU, and JIAFENG LIU. "A HYBRID POST-PROCESSING SYSTEM FOR HANDWRITTEN CHINESE CHARACTER RECOGNITION." International Journal of Pattern Recognition and Artificial Intelligence 16, no. 06 (2002): 657–79. http://dx.doi.org/10.1142/s0218001402001964.

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In this paper, a hybrid post-processing system for improving the performance of Handwritten Chinese Character Recognition is presented. In order to remove two kinds of frequently encountered errors in the recognition result, namely mis-recognized character and unrecognized character, both confusing character characteristics of the recognizer and the contextual linguistic information are utilized in our hybrid three-stage post-processing system. In the first stage, the confusing character set and a statistical Noisy-Channel model are employed to identify the most promising candidate character a
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20

Srhoj, Dejan. "I don’t do performances, I’m a dancer." Maska 36, no. 203 (2021): 14–21. http://dx.doi.org/10.1386/maska_00068_7.

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I poured myself a bit of rakija, everyone in the flat was asleep, the light was dim and almost no sounds entered from the outside. I was browsing through documents, thoughts, photos and audio collages of Chrysa’s research project ‘Documenting experimental authorship’. I was listening to her podcast titled Value of Dance as Practice. I got immersed in her voice, in handwritten pages, in words that became poetry, in details of space that shape her dance. And after a very long time I felt someone was speaking my language, the language of a dancer. I knew I had to talk to her. The following interv
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Toleushova, A. T., D. M. Uypalakova, and A. B. Imansakipova. "SIGNATURE RECOGNITION ALGORITHMS. BEZIER ALGORITHM." Bulletin of Shakarim University. Technical Sciences, no. 3(7) (February 10, 2023): 47–53. http://dx.doi.org/10.53360/2788-7995-2022-1(5)-7.

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This article focuses on improving the human and machine interface, which should ensure efficient processing of data and knowledge in simple, fast and accessible ways. One of the ways to organize it is the introduction of the manuscript (entering text, drawings, drawings, etc.). Handwritten signatures can be considered as handwritten words, but they are more suitable for drawings, because the signer tries to make his signature unique, using not only his first and last names, but also additional graphic elements. Creating a signature is quite simple, although it is impossible to reproduce the re
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Jуźwikiewicz, Przemysław. "THE INFLUENCE OF DISTANCE LEARNING ON THE STUDY OF STYLISTICS OF THE UKRAINIAN LANGUAGE (Wroclaw experience)." Theory and Practice of Teaching Ukrainian as a Foreign Language, no. 15 (May 1, 2021): 29–39. http://dx.doi.org/10.30970/ufl.2021.15.3279.

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The article describes the influence of online teaching on the learning of Ukrainian stylistics. Apart from addressing the theoretical issues concerning online teaching and the teaching of Ukrainian stylistics, the article presents the characteristics of teaching this course (including the course contents) at the Institute of Slavic Studies at the University of Wrocław. The analysis of the problem was based on a survey conducted among MA students of Ukrainian studies at the University of Wrocław, who partially (in the summer semester of the academic year 2019/20220) or fully (in the academic ye
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Bhattacharya, Nilanjana, Partha Pratim Roy, Umapada Pal, and Sanjit Kumar Setua. "ONLINE BANGLA HANDWRITTEN WORD RECOGNITION." Malaysian Journal of Computer Science 31, no. 4 (2018): 300–310. http://dx.doi.org/10.22452/mjcs.vol31no4.4.

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Vaculínová, Marta. "Osobní hesla humanistů, jejich funkce, formy a využití v provenienčním výzkumu." Acta Musei Nationalis Pragae – Historia litterarum 67, no. 1-2 (2022): 50–61. http://dx.doi.org/10.37520/amnpsc.2022.007.

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The personal mottos of intellectuals, called symbola, came into greater use under the influence of the Italian Renaissance and its ideas of true nobility, which is not acquired by descent but by education and virtue. Inspired by noblemen, scholars created their own personal representations, among the most common being personal devices, followed by emblems and portraits. The first symbols in the Czech lands are known to have appeared at the beginning of the 16th century, but their use truly developed in the Rudolphine period. Court intellectuals, university professors, teachers, clergymen and e
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Patil, Prachi, and Saniya Ansari. "Online Handwritten Devnagari Word Recognition using HMM based Technique." International Journal of Computer Applications 95, no. 17 (2014): 17–21. http://dx.doi.org/10.5120/16686-6802.

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Simayi, Wujiahemaiti, Mayire Ibrahim, Xu-Yao Zhang, Cheng-Lin Liu, and Askar Hamdulla. "A benchmark for unconstrained online handwritten Uyghur word recognition." International Journal on Document Analysis and Recognition (IJDAR) 23, no. 3 (2020): 205–18. http://dx.doi.org/10.1007/s10032-020-00354-0.

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Sen, Shibaprasad, Ankan Bhattacharyya, Mridul Mitra, Kaushik Roy, Sudip Kumar Naskar, and Ram Sarkar. "Online Bangla handwritten word recognition using HMM and language model." Neural Computing and Applications 32, no. 14 (2019): 9939–51. http://dx.doi.org/10.1007/s00521-019-04518-w.

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QUINIOU, SOLEN, FRANÇOIS BOUTERUCHE, and ERIC ANQUETIL. "WORD EXTRACTION ASSOCIATED WITH A CONFIDENCE INDEX FOR ONLINE HANDWRITTEN SENTENCE RECOGNITION." International Journal of Pattern Recognition and Artificial Intelligence 23, no. 05 (2009): 945–66. http://dx.doi.org/10.1142/s0218001409007442.

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This paper presents a word extraction approach based on the use of a confidence index to limit the total number of segmentation hypotheses in order to further extend our online sentence recognition system to perform "on-the-fly" recognition. Our initial word extraction task is based on the characterization of the gap between each couple of consecutive strokes from the online signal of the handwritten sentence. A confidence index is associated to the gap classification result in order to evaluate its reliability. A reconsideration process is then performed to create additional segmentation hypo
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CAILLAULT, EMILIE, and CHRISTIAN VIARD-GAUDIN. "MIXED DISCRIMINANT TRAINING OF HYBRID ANN/HMM SYSTEMS FOR ONLINE HANDWRITTEN WORD RECOGNITION." International Journal of Pattern Recognition and Artificial Intelligence 21, no. 01 (2007): 117–34. http://dx.doi.org/10.1142/s0218001407005338.

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Online handwritten word recognition systems usually rely on Hidden Markov Models (HMMs), which are effective under many circumstances, but suffer some major limitations in real world applications. Artificial neural networks (ANN) appear to be a promising alternative, however they failed to model sequence data such as online handwriting due to their variable lengths. As a consequence, by combining HMMs and ANN, we can expect to take advantage of the robustness and flexibility of the HMMs generative models and of the discriminative power of the ANN. Training such a hybrid system is not straightf
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Garcia-Salicetti, Sonia, Bernadette Dorizzi, Patrick Gallinari, and Zsolt Wimmer. "Maximum mutual information training for an online neural predictive handwritten word recognition system." International Journal on Document Analysis and Recognition 4, no. 1 (2001): 56–68. http://dx.doi.org/10.1007/pl00013574.

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Bharath, A., and S. Madhvanath. "HMM-Based Lexicon-Driven and Lexicon-Free Word Recognition for Online Handwritten Indic Scripts." IEEE Transactions on Pattern Analysis and Machine Intelligence 34, no. 4 (2012): 670–82. http://dx.doi.org/10.1109/tpami.2011.234.

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Ghosh, Rajib, Chirumavila Vamshi, and Prabhat Kumar. "RNN based online handwritten word recognition in Devanagari and Bengali scripts using horizontal zoning." Pattern Recognition 92 (August 2019): 203–18. http://dx.doi.org/10.1016/j.patcog.2019.03.030.

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Baldominos, Alejandro, Yago Saez, and Pedro Isasi. "A Survey of Handwritten Character Recognition with MNIST and EMNIST." Applied Sciences 9, no. 15 (2019): 3169. http://dx.doi.org/10.3390/app9153169.

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This paper summarizes the top state-of-the-art contributions reported on the MNIST dataset for handwritten digit recognition. This dataset has been extensively used to validate novel techniques in computer vision, and in recent years, many authors have explored the performance of convolutional neural networks (CNNs) and other deep learning techniques over this dataset. To the best of our knowledge, this paper is the first exhaustive and updated review of this dataset; there are some online rankings, but they are outdated, and most published papers survey only closely related works, omitting mo
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Singh, Sukhdeep, Anuj Sharma, and Vinod Kumar Chauhan. "Online handwritten Gurmukhi word recognition using fine-tuned Deep Convolutional Neural Network on offline features." Machine Learning with Applications 5 (September 2021): 100037. http://dx.doi.org/10.1016/j.mlwa.2021.100037.

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Ibrayim, Mayire, Wujiahematiti Simayi, and Askar Hamdulla. "Unconstrained online handwritten Uyghur word recognition based on recurrent neural networks and connectionist temporal classification." International Journal of Biometrics 13, no. 1 (2021): 51. http://dx.doi.org/10.1504/ijbm.2021.10034249.

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Ibrayim, Mayire, Wujiahematiti Simayi, and Askar Hamdulla. "Unconstrained online handwritten Uyghur word recognition based on recurrent neural networks and connectionist temporal classification." International Journal of Biometrics 13, no. 1 (2021): 51. http://dx.doi.org/10.1504/ijbm.2021.112216.

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Kumar, Dinesh, and Neeta Rana. "Speech Synthesis System for Online Handwritten Punjabi Word: An Implementation of SVM and Concatenative TTS." International Journal of Computer Applications 26, no. 2 (2011): 13–17. http://dx.doi.org/10.5120/3077-4211.

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Ansari, Saniya, Bhavani S, and Udaysingh Sutar. "A NOVEL APPROACH TOWARDS ONLINE DEVNAGARI HANDWRITTEN WORD RECOGNITION BASED ON ROBUST FEATURE EXTRACTION METHOD AND FFNN CLASSIFIER." International Journal of Advanced Research 5, no. 8 (2017): 764–76. http://dx.doi.org/10.21474/ijar01/5117.

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Ghosh, Rajib, Partha Pratim Roy, and Prabhat Kumar. "Smart Device Authentication Based on Online Handwritten Script Identification and Word Recognition in Indic Scripts Using Zone-Wise Features." International Journal of Information System Modeling and Design 9, no. 1 (2018): 21–55. http://dx.doi.org/10.4018/ijismd.2018010102.

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Secure authentication is a vital component for device security. The most basic form of authentication is by using passwords. With the evolution of smart devices, selecting stronger and unbreakable passwords have become a challenging task. Such passwords if written in native languages tend to offer improved security since attackers having no knowledge of such scripts finding it hard to crack. This article proposes two zone-wise feature extraction approaches - zone-wise structural and directional (ZSD) and zone-wise slopes of dominant points (ZSDP), to recognize online handwritten script and wor
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Dicinoski, Michelle. "Digital Archives and Cultural Memory: Discovering Lost Histories in Digitised Australian Children’s Literature 1851–1945." Papers: Explorations into Children's Literature 22, no. 1 (2012): 110–20. http://dx.doi.org/10.21153/pecl2012vol22no1art1135.

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 The full-text digitisation of literary works can have some unexpected benefits for researchers in and outside of the field of literary studies. While the broader availability and easier distribution of the text is a clear and intended result of digitisation, the preservation of extra-textual material—such as bookplates, inscriptions, advertisements, and marginal notes—is an unintended result that can help to expand our knowledge of literary networks, reading practices, and cultural history. This kind of material was preserved by the Children’s Literature Digital Resources
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Xu, Siqiu, Xi Li, Chenchen Xie, Houpeng Chen, Cheng Chen, and Zhitang Song. "A High-Precision Implementation of the Sigmoid Activation Function for Computing-in-Memory Architecture." Micromachines 12, no. 10 (2021): 1183. http://dx.doi.org/10.3390/mi12101183.

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Computing-In-Memory (CIM), based on non-von Neumann architecture, has lately received significant attention due to its lower overhead in delay and higher energy efficiency in convolutional and fully-connected neural network computing. Growing works have given the priority to researching the array of memory and peripheral circuits to achieve multiply-and-accumulate (MAC) operation, but not enough attention has been paid to the high-precision hardware implementation of non-linear layers up to now, which still causes time overhead and power consumption. Sigmoid is a widely used non-linear activat
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Moysey, Antoniy. "The scientific heritage of Dimitriy Dan and his printed works bibliographical index (1875–1927)." Current issues of social sciences and history of medicine, no. 2 (August 14, 2023): 48–59. http://dx.doi.org/10.24061/2411-6181.2.2022.352.

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The article is another step in the research of the scientific creativity of Bukovyna priest, historian, ethnologist, corresponding member of the Romanian Academy of Sciences Dimitriy Dan (1856–1927). The fact of international recognition of his works is undeniable, not to mention the use of his creative heritage in Ukrainian and Romanian historiography. But, unfortunately, today there are no special bibliographic studies, a complete list of printed scientific and scientific journalistic works of the tireless scientist. Therefore, the purpose of this study is to compile a bibliographic index of
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Pan, Yuecai, Daoerji Fan, Huijuan Wu, and Da Teng. "A new dataset for mongolian online handwritten recognition." Scientific Reports 13, no. 1 (2023). http://dx.doi.org/10.1038/s41598-022-27267-8.

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AbstractThis paper introduces a new traditional Mongolian word-level online handwriting dataset, MOLHW. The dataset consists of handwritten Mongolian words, including 164,631 samples written by 200 writers and covering 40,605 Mongolian common words. These words were selected from a large Mongolian corpus. The coordinate points of words were collected by volunteers, who wrote the corresponding words on the dedicated application for their mobile phones. Latin transliteration of Mongolian was used to annotate the coordinates of each word. At the same time, the writer’s identification number and m
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Tabassum, Shaira, Nuren Abedin, Md Mahmudur Rahman, et al. "An online cursive handwritten medical words recognition system for busy doctors in developing countries for ensuring efficient healthcare service delivery." Scientific Reports 12, no. 1 (2022). http://dx.doi.org/10.1038/s41598-022-07571-z.

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AbstractDoctors in developing countries are too busy to write digital prescriptions. Ninety-seven percent of Bangladeshi doctors write handwritten prescriptions, the majority of which lack legibility. Prescriptions are harder to read as they contain multiple languages. This paper proposes a machine learning approach to recognize doctors’ handwriting to create digital prescriptions. A ‘Handwritten Medical Term Corpus’ dataset is developed containing 17,431 samples of 480 medical terms. In order to improve the recognition efficiency, this paper introduces a data augmentation technique to widen t
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Bhardwaj, Naman. "A Research on Handwritten Text Recognition." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 06, no. 04 (2022). http://dx.doi.org/10.55041/ijsrem12649.

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Over the years we have started accumulating handwritten documents, like pdfs, doc files and numerous other formats for reading, writing and studying. Often we come across situations where we need to utilize the text of those documents. Manually transcribing large amounts of handwritten data is an arduous process that’s bound to be fraught with errors. Automated handwriting recognition can drastically cut down on the time required to transcribe large volumes of text, and also serve as a framework for developing future applications of machine learning. Recognition can be offline or online and bo
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Ibrayim, Mayire, Askar Hamdulla, and Dilmurat Tursun. "A Dynamic Programming Method for Segmentation of Online Cursive Uyghur Handwritten Words into Basic Recognizable Units." Journal of Software 8, no. 10 (2013). http://dx.doi.org/10.4304/jsw.8.10.2535-2540.

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HP, Abhishek, Jayashree CS, Megna Gokul, and Bhavani B. "Handwritten Character Recognition through Feature Extraction using Artificial Neural Networks." Advances in Intelligent Systems and Technologies, December 6, 2022, 61–68. http://dx.doi.org/10.53759/aist/978-9914-9946-1-2_12.

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Today’s computer can be fast, accurate and knowledgeable. But they are far from being intelligent; computers are still unable to communicate with human beings in natural forms like written languages, speeches, pictures and images. With the rapid development in the computer facilities users have now turned their attention to interact with computers in their local languages, so it is more user friendly. In Karnataka, HINDI is the local and official language. it is very convenient and faster to enter a HINDI document into computer by handwriting rather than by typing using existing HINDI converte
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48

Dr. Manjunatha S. "DIGITALISATION OF LIBRARIES (DIGITAL LIBRARIES) AND ITS SCOPE." EPRA International Journal of Research & Development (IJRD), July 7, 2022, 40–42. http://dx.doi.org/10.36713/epra10724.

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In comparison to traditional libraries, digital libraries provide efficient and qualitative services by collecting, organizing, storing, disseminating, retrieving and preserving the information. Digital libraries support preservation besides making information retrieval and delivery more comfortable. It provides online access to historical and cultural documents whose existence is endangered due to physical decay. The major areas which offer digital libraries great exploitation are: Information retrieval, multimedia database, data mining, data warehouse, on-line information repositories, image
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49

Simayi, Wujiahemaiti, Mayire Ibrayim, and Askar Hamdulla. "Study the preprocessing effect on RNN based online Uyghur handwritten word recognition." Wireless Networks, June 1, 2021. http://dx.doi.org/10.1007/s11276-021-02651-w.

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50

Simayi, Wujiahemaiti, Mayire Ibrayim, and Askar Hamdulla. "Character type based online handwritten Uyghur word recognition using recurrent neural network." Wireless Networks, June 1, 2021. http://dx.doi.org/10.1007/s11276-021-02650-x.

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