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Dissertations / Theses on the topic 'Handwritten Sindhi character recognition'

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Published: 7 June 2025

Last updated: 16 July 2025

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1

Chai, Sin-Kuo. "Multiclassifier neural networks for handwritten character recognition." Ohio : Ohio University, 1995. http://www.ohiolink.edu/etd/view.cgi?ohiou1174331633.

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2

Clarke, Eddie. "A novel approach to handwritten character recognition." Thesis, University of Nottingham, 1995. http://eprints.nottingham.ac.uk/14035/.

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A number of new techniques and approaches for off-line handwritten character recognition are presented which individually make significant advancements in the field. First. an outline-based vectorization algorithm is described which gives improved accuracy in producing vector representations of the pen strokes used to draw characters. Later. Vectorization and other types of preprocessing are criticized and an approach to recognition is suggested which avoids separate preprocessing stages by incorporating them into later stages. Apart from the increased speed of this approach. it allows more ef

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3

Xu, Zhengyan, and Yibing Zhou. "Specific Handwritten Chinese Character Recognition Based on Artificial Intelligence." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-14599.

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As internet techniques are developing more and more quickly, internet becomes the main way to communicate with the outside world. In this case, written information on paper needs to be converted to digital information urgently, increasing the need for handwritten character recognition. The aim of this work is to discuss methods that can be used to recognize handwritten Chinese characters. We study geometric features and clustering of handwritten Chinese characters from three aspects, which are handwritten character preprocessing, feature extraction and clustering. To test the correctness of ou

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4

Sawhney, Sumeet S. "Distance measurements and their combination in handwritten character recognition." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ59339.pdf.

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5

Ansari, Nasser. "Handwritten character recognition by using neural network based methods." Ohio : Ohio University, 1992. http://www.ohiolink.edu/etd/view.cgi?ohiou1172080742.

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6

陳國評 and Kwok-ping Chan. "Fuzzy set theoretic approach to handwritten Chinese character recognition." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1989. http://hub.hku.hk/bib/B30425876.

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7

Sahai, Anant. "Handwritten character recognition using the minimum description length principle." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/11015.

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8

Shi, Daming. "An active radical approach to handwritten Chinese character recognition." Thesis, University of Southampton, 2002. https://eprints.soton.ac.uk/257379/.

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9

Wang, Jianguo. "Off-line computer recognition of unconstrained handwritten characters." Thesis, The University of Sydney, 2001. https://hdl.handle.net/2123/27805.

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This thesis presents several techniques for improving the performance of off—line Optical Character Recognition (OCR) systems: broken character mending and recognition, feature extraction methods in OCR and hybrid methods for handwritten numeral recognition. As an application, form document image compression and indexing is also introduced. Broken characters mending techniques are investigated first. A macrostrtrcture analysis (MSA) mending method is proposed based on skeleton and boundary information and macrostructure analysis that investigates the stroke tendency and other propert

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10

Manley-Cooke, Peter. "Handwritten character recognition using a multi-classifier neuro-fuzzy framework." Thesis, University of East Anglia, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.433914.

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11

Kassel, Robert H. "A comparison of approaches to on-line handwritten character recognition." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11407.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.<br>Includes bibliographical references (p. 155-163).<br>by Robert Howard Kassel.<br>Ph.D.

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12

Kunwar, Rituraj. "Incremental / Online Learning and its Application to Handwritten Character Recognition." Thesis, Griffith University, 2017. http://hdl.handle.net/10072/366964.

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In real world scenarios where we use machine learning algorithms, we often have to deal with cases where input data changes its nature with time. In order to maintain the accuracy of the learning algorithm, we frequently have to retrain our learning system, thereby making the system inconvenient and unreliable. This problem can be solved by using learning algorithms which can learn continuously with time (incremental/ online learning). Another common problem of real-world learning scenarios that we often have to deal with is acquiring large amounts of data which is expensive and time consuming

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13

He, Tingting, and 何婷婷. "A study on several problems in online handwritten Chinese character recognition." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B42182086.

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14

He, Tingting. "A study on several problems in online handwritten Chinese character recognition." Click to view the E-thesis via HKUTO, 2008. http://sunzi.lib.hku.hk/hkuto/record/B42182086.

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15

Chen, Wen-Tsong. "Word level training of handwritten word recognition systems /." free to MU campus, to others for purchase, 2000. http://wwwlib.umi.com/cr/mo/fullcit?p9974612.

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16

Zhao, Mengqiao. "Handwritten digit recognition based on segmentation-free method." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20685.

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This thesis aims to implement a segmentation-free strategy in the context of handwritten multi-digit string recognition. Three models namely VGG-16, CRNN and 4C are built to be evaluated and benchmarked, also research about the effect of the different training set on model performance is carried out.

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17

Morns, Ian Philip. "The novel dynamic supervised forward propagation neural network for handwritten character recognition." Thesis, University of Newcastle Upon Tyne, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285741.

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18

Kabir, Ehsanollah. "Application of domain knowledge to recognition of hand-printed and handwritten postal addresses." Thesis, University of Essex, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.236248.

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19

Junaidi, Akmal [Verfasser], Gernot A. [Akademischer Betreuer] Fink, and Heinrich [Gutachter] Müller. "Lampung handwritten character recognition / Akmal Junaidi ; Gutachter: Heinrich Müller ; Betreuer: Gernot A. Fink." Dortmund : Universitätsbibliothek Dortmund, 2016. http://d-nb.info/1131355199/34.

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20

Rahman, Ahmad Fuad Rezaur. "Study of multiple expert decision combination strategies for handwritten and printed character recognition." Thesis, University of Kent, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.245624.

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21

Junaidi, Akmal [Verfasser], Gernot A. Akademischer Betreuer] Fink, and Heinrich [Gutachter] [Müller. "Lampung handwritten character recognition / Akmal Junaidi ; Gutachter: Heinrich Müller ; Betreuer: Gernot A. Fink." Dortmund : Universitätsbibliothek Dortmund, 2016. http://nbn-resolving.de/urn:nbn:de:101:1-201705052915.

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22

Mohan, Sumod K. "Accuracy and multi-core performance of machine learning algorithms for handwritten character recognition." Connect to this title online, 2009. http://etd.lib.clemson.edu/documents/1252424826/.

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23

Monger, David M. "The human factors aspects of interactive document image description for OCR of handwritten forms." Thesis, University of Essex, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.238747.

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24

Bonnici, Elias, and Per Arn. "The impact of Data Augmentation on classification accuracy and training time in Handwritten Character Recognition." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302538.

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This bachelor thesis was conducted at the Royal Institute of Technology with the purpose of examining several combinations of data augmentation methods and their impact on classification accuracy of a CNN model. Further, the study investigates the time taken to train the model using the different data augmentation methods as to decide which ones have the best impact on classification accuracy in relation to their computational cost. The results indicate that the best classification accuracy is achieved when applying all provided augmentation methods although this leads to the longest training

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25

Prum, Sophea. "On the use of a discriminant approach for handwritten word recognition based on bi-character models." Thesis, La Rochelle, 2013. http://www.theses.fr/2013LAROS418/document.

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Avec l’avènement des dispositifs nomades tels que les smartphones et les tablettes, la reconnaissance automatique de l’écriture manuscrite cursive à partir d’un signal en ligne est devenue durant les dernières décennies un besoin réel de la vie quotidienne à l’ère numérique. Dans le cadre de cette thèse, nous proposons de nouvelles stratégies pour un système de reconnaissance de mots manuscrits en-ligne. Ce système se base sur une méthode collaborative segmentation/reconnaissance et en utilisant des analyses à deux niveaux : caractère et bi-caractères. Plus précisément, notre système repose su

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26

Nederhof, Mark-Jan. "OCR of hand-written transcriptions of hieroglyphic text." Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-201704.

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Encoding hieroglyphic texts is time-consuming. If a text already exists as hand-written transcription, there is an alternative, namely OCR. Off-the-shelf OCR systems seem difficult to adapt to the peculiarities of Ancient Egyptian. Presented is a proof-of-concept tool that was designed to digitize texts of Urkunden IV in the hand-writing of Kurt Sethe. It automatically recognizes signs and produces a normalized encoding, suitable for storage in a database, or for printing on a screen or on paper, requiring little manual correction. The encoding of hieroglyphic text is RES (Revised Encoding Sch

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27

Noghe, Petr. "Vyhodnocení testových formulářů pomocí OCR." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-219986.

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This thesis deals with the evaluation forms using optical character recognition. Image processing and methods used for OCR is described in the first part of thesis. In the practical part is created database of sample characters. The chosen method is based on correlation between patterns and recognized characters. The program is designed in a graphical environment MATLAB. Finally, several forms are evaluated and success rate of the proposed program is detected.

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Hříbek, David. "Active Learning pro zpracování archivních pramenů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445535.

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This work deals with the creation of a system that allows uploading and annotating scans of historical documents and subsequent active learning of models for character recognition (OCR) on available annotations (marked lines and their transcripts). The work describes the process, classifies the techniques and presents an existing system for character recognition. Above all, emphasis is placed on machine learning methods. Furthermore, the methods of active learning are explained and a method of active learning of available OCR models from annotated scans is proposed. The rest of the work deals

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29

Ms, Shalini. "Handwritten Hindi Character Recognition." Thesis, 2017. http://ethesis.nitrkl.ac.in/8879/1/2017_MT_Shalini.pdf.

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Devanagari, the most accepted script in India and Hindi is the only dialect which is widely spoken and written, so Handwritten Hindi character Recognition is done. Optical Character Recognition (OCR) is used for pattern recognition, it can be online or offline. Handwritten text is electronically converted into machine learning language. Handwritten character Recognition has many applications like cheque reader,passport reader,address reader,specific tasks readers. Devanagari is troublesome because the characters present in a words are somewhat similar to other character or connected words may

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30

Chen, Ching-Yi, and 陳慶逸. "Off-line Handwritten Character Recognition." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/78087161407572953101.

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碩士<br>淡江大學<br>電機工程學系研究所<br>86<br>In this thesis , we propose a new scheme for off-line recognition of totallyun constrained handwritten characters using SOM/LVQ neural networks and extractio ngfeature vectors by kirsch masks method. In the learning phase, the SOM neura l networks is used to cluster the feature vectors into several classes. In the recognitionstage, the learning results of the neural networks are utilized to identify the inputdata. In order to seek the optium cluster set, the resultin g c

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31

Sharma, Anand. "Devanagari Online Handwritten Character Recognition." Thesis, 2019. https://etd.iisc.ac.in/handle/2005/4633.

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In this thesis, a classifier based on local sub-unit level and global character level representations of a character, using stroke direction and order variations independent features, is developed for recognition of Devanagari online handwritten characters. It is shown that online character corresponding to Devanagari ideal character can be analyzed and uniquely represented in terms of homogeneous sub-structures called the sub-units. These sub-units can be extracted using direction property of online strokes in an ideal character. A method for extraction of sub-units from a handwritten c

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32

ISLAM, ZAHIRUL. "HANDWRITTEN CHARACTER RECOGNITION OF ASSAMESE HANDWRITTEN RECOGNITION USING CONVOLUTION NEURAL NETWORK." Thesis, 2022. http://dspace.dtu.ac.in:8080/jspui/handle/repository/19249.

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The involvement of technology is reshaping our perception of the world. The inherent desire to understand human consciousness and intelligence has led to the widespread development of the fields like Artificial Intelligence and Machine learning. [1] Artificial intelligence has paved its way into most disciplines and blended in as an essential tool to boost efficiency and non-conventional enhancements. Linguistics is one such field; with the involvement of AI, communication and text extraction have become vividly easier. The presented work involves the development of one such applic

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33

Ghabrial, Melad Y. "Parallel algorithms for handwritten character recognition." Thesis, 1990. http://spectrum.library.concordia.ca/3859/1/MM97702.pdf.

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34

"Video-based handwritten Chinese character recognition." 2003. http://library.cuhk.edu.hk/record=b6073522.

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by Lin Feng.<br>"June 2003."<br>Thesis (Ph.D.)--Chinese University of Hong Kong, 2003.<br>Includes bibliographical references (p. [114]-130).<br>Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.<br>Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.<br>Mode of access: World Wide Web.<br>Abstracts in English and Chinese.

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35

CAI, YU-SHENG, and 蔡玉生. "Handwritten character recognition by graph matching." Thesis, 1988. http://ndltd.ncl.edu.tw/handle/98437928794972396263.

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36

LI, HUEY JIUAN, and 李惠娟. "Part orientation for handwritten character recognition." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/89931911197348736715.

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碩士<br>國立中山大學<br>應用數學研究所<br>84<br>A regional decomposition method and a hierarchical model without consideration of orientation have been proposed to investigate the recognition rates of patterns in [1-4]. In this thesis, new models with orientations at various positions have been proposed to produce a more complete character recognizer, based on the probability of occurrence of the patterns.New formulas are developed to evaluate the recognition rates of non- fix orientation from those of fi

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37

Hoi, Chu-Chong, and 許主聰. "A Study on Handwritten Character Recognition." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/04065851585956727358.

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碩士<br>臺灣大學<br>資訊工程學研究所<br>98<br>There are many applications for handwritten character recognition, such as signature verification, handwritten address recognition, pen-based input method used in PDA etc. In this thesis, we just consider offline character recognition because it is the basic building block of many complicate handwriting recognition system. We compare four techniques for handwritten recognition. They are PCA, LDA, NMF and ICA. The result shows that PCA has the highest accuracy. LDA has the lowest accuracy due to small training data set. The difference of performance between ICA a

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38

KUMAR, PRAJJWAL. "HANDWRITTEN CHARACTER RECOGNITION USING DEEP LEARNING." Thesis, 2022. http://dspace.dtu.ac.in:8080/jspui/handle/repository/19136.

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Handwritten character identification is a topic that has been researched for years and is an area of interest for the community of Pattern recognition researchers since It may be put to use in a wide range of fascinating applications. all across the field. This subject is a difficult challenge as a task because each person has their own unique writing style. SVM, ANN, and CNN models are some of the available options for handling this problem's many different ways and approaches. HCR is a need in the modern world since it assists us in a variety of fields of public domain, which mak

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KUMAR, PRAJJWAL. "HANDWRITTEN CHARACTER RECOGNITION USING DEEP LEARNING." Thesis, 2022. http://dspace.dtu.ac.in:8080/jspui/handle/repository/19407.

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Handwritten character identification is a topic that has been researched for years and is an area of interest for the community of Pattern recognition researchers since It may be put to use in a wide range of fascinating applications. all across the field. This subject is a difficult challenge as a task because each person has their own unique writing style. SVM, ANN, and CNN models are some of the available options for handling this problem's many different ways and approaches. HCR is a need in the modern world since it assists us in a variety of fields of public domain, which mak

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40

"Perspectives of pattern recognition in handwritten character recognition." Tulane University, 1995.

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Handwritten Character Recognition is a long-standing problem among computer scientists. It promises several benefits to the user friendliness of modern computers. Several classical pattern recognition methods such as template matching, Fourier transformation, geometric moments and scene analysis which have proven to be effective in several domains have not yielded consistent or reliable results for handwritten character recognition Currently, neural networks are considered as the underlying computing mechanism for a robust approach to the problem of handwritten character recognition. This thes

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41

Shu-Ling, Chao, and 趙素玲. "Neural Networks on Handwritten Alphanumeric Character Recognition." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/68960372869420102061.

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碩士<br>靜宜大學<br>管理科學研究所<br>82<br>Handwritten Character recognition is a well-know complicated but intersting problem. Although numerous efforts have been made based on traditional computers, they are still suffered by eith- er time-consumed procedure or imperfect recognition rate. In th- esis, a new approach based on neural networks for recognition of unconstrained handwritten alphanumeric characters is proposed and implemented.The hybrid system consists of a kernel subsystem which is based o

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42

GUO, SHI-CHONG, and 郭世崇. "Handwritten Chinese character recognition via neural network." Thesis, 1992. http://ndltd.ncl.edu.tw/handle/18937680590489760523.

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Chan, Tung Jung, and 詹東融. "Statistical off line handwritten Chinese character recognition." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/07969728621521247131.

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王仁裕. "Handwritten Chinese Character Recognition by Neural Networks." Thesis, 1990. http://ndltd.ncl.edu.tw/handle/56580673553701061169.

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45

Wu, Shin-Hao, and 吳欣澔. "Handwritten Alphanumeric Character Recognition with Low Ambiguity." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/98421832847713254465.

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碩士<br>國立交通大學<br>多媒體工程研究所<br>103<br>The goal of this thesis is to recognize handwritten character with low ambiguity. In order to solve the problem that handwritten characters has too much stroke order, we use computer to analysis the skeleton of character image and get unify stroke order. So, character similar in shape will have same stroke order. This system is composed of into three steps. In the first steps, we find the major skeleton of the character image based on Morphology, and get thinned character image. In the second step, we trace the thinned character image to get stroke order of

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Hong-De, Chang, and 張鴻德. "A Study on Handwritten Chinese Character Recognition." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/65194069833122183642.

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博士<br>國立成功大學<br>電機工程研究所<br>82<br>Handwritten Chinese character recognition was once considered to be a very difficult problem and regarded as one of the goals of character recognition research. The proposed system contains four main steps: preprocessing, feature extraction, preclassification, and recognition. First of all, the some operations are performed to obtain a suitable data formate. the number of Chinese characters is very large, preclassification stage is usually needed for this wo

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Hua, Chen Bo, and 陳柏樺. "Handwritten Character Recognition using GA-based CNN." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/69041942101896744315.

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碩士<br>國立高雄應用科技大學<br>電機工程系<br>99<br>In this paper, the static simulation method is used for handwritten characters recognition. Since a lot of noise and some non-character traces would occur while scanning image of writting characters, it evoked an inevitable noise-elimination problems in character recognition. This paper simulates the image preprocessing by adding several types of noise, and then filter it out by using conventional and gene-based CNN methods. The results demonstrate the superiority of CNN optimization method. In dealing with salt-pepper noise and Gaussian noise, CNN algorithm

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ZENG, LING-QI, and 曾令祺. "Handwritten Character Recognition Loading in Hopfield Model." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/9wyjk4.

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碩士<br>國立臺灣大學<br>資訊網路與多媒體研究所<br>106<br>Nowadays, handwriting recognition systems has been applied to all aspects of industries and social life. Each feature of a radical or a pattern is represented by a five dimensional vector called Bended-ellipse feature which including the coordinates the direction, the angle, and the lengths information. Once the features are generated, they will find the topological relations between those features. We simply obtain a feature-to-feature (FTF) order by define the “neighbor” of the features. After obtaining bended-ellipse features and FTF order information,

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Cheng, Rei-Heng, and 鄭瑞��. "Handwritten Chinese character recognition based on structural relations of character strokes." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/10443923778682920845.

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博士<br>國立交通大學<br>資訊工程研究所<br>83<br>This dissertation is concerned with handwritten Chinese character recognition problem. In the first part, we propose a problem reduction technique to reduce the radical recognition problem to a subproblem of recognizing stable stroke substructure(s) in the radical. Furthermore, the stroke substructure recognition problem can be further reduced to a subproblem of identifying a salient stroke in each stroke substructure. Th

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CHEN, YUAN-ZHONG, and 陳元中. "Performance analysis of character recognition systems via handwritten chinese character generator." Thesis, 1992. http://ndltd.ncl.edu.tw/handle/25970235394443528978.

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