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Journal articles on the topic 'Font feature'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 July 2025

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1

Zhu, Xuanying, Mugang Lin, Kunhui Wen, Huihuang Zhao, and Xianfang Sun. "Deep Deformable Artistic Font Style Transfer." Electronics 12, no. 7 (2023): 1561. http://dx.doi.org/10.3390/electronics12071561.

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The essence of font style transfer is to move the style features of an image into a font while maintaining the font’s glyph structure. At present, generative adversarial networks based on convolutional neural networks play an important role in font style generation. However, traditional convolutional neural networks that recognize font images suffer from poor adaptability to unknown image changes, weak generalization abilities, and poor texture feature extractions. When the glyph structure is very complex, stylized font images cannot be effectively recognized. In this paper, a deep deformable

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LEE, CHANG WOO, HYUN KANG, HANG JOON KIM, and KEECHUL JUNG. "FONT CLASSIFICATION USING NMF WITH HIERARCHICAL CLUSTERING." International Journal of Pattern Recognition and Artificial Intelligence 19, no. 06 (2005): 755–73. http://dx.doi.org/10.1142/s0218001405004307.

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The current paper proposes a font classification method for document images that uses non-negative matrix factorization (NMF), that is able to learn part-based representations of objects. The basic idea of the proposed method is based on the fact that the characteristics of each font are derived from parts of individual characters in each font rather than holistic textures. Spatial localities, parts composing of font images, are automatically extracted using NMF and, then, used as features representing each font. Using hierarchical clustering algorithm, these feature sets are generalized for f

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Mashagba, Eman Fares Al. "Human Identification Based on Geometric Feature Extraction Using a Number of Biometric Systems Available: Review." Computer and Information Science 9, no. 2 (2016): 140. http://dx.doi.org/10.5539/cis.v9n2p140.

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<span style="font-size: 10.5pt; font-family: 'Times New Roman','serif'; mso-ansi-language: EN-US; mso-bidi-font-size: 12.0pt; mso-fareast-font-family: 宋体; mso-font-kerning: 1.0pt; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">Biometric technology has attracted much attention in biometric recognition. Significant online and offline applications satisfy security and human identification based on this technology. Biometric technology identifies a human based on unique features possessed by a person. Biometric features may be physiological or behavioral. A physiologica

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Zhao, Hong, Jinhai Huang, Wengai Li, Zhaobin Chang, and Weijie Wang. "PSA-HWT: handwritten font generation based on pyramid squeeze attention." PeerJ Computer Science 10 (August 23, 2024): e2261. http://dx.doi.org/10.7717/peerj-cs.2261.

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The generator, which combines convolutional neural network (CNN) and Transformer as its core modules, serves as the primary model for the handwriting font generation network and demonstrates effective performance. However, there are still problems with insufficient feature extraction in the overall structure of the font, the thickness of strokes, and the curvature of strokes, resulting in subpar detail in the generated fonts. To solve the problems, we propose a method for constructing a handwritten font generation model based on Pyramid Squeeze Attention, called PSA-HWT. The PSA-HWT model is d

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Qomariyah, Fitriyatul, Fitri Utaminingrum, and Muchlas Muchlas. "Handwriting Arabic Character Recognition Using Features Combination." IJID (International Journal on Informatics for Development) 10, no. 2 (2021): 62–71. http://dx.doi.org/10.14421/ijid.2021.2360.

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The recognition of Arabic handwriting is a challenging problem to solve. The similarity among the fonts appears as a problem in the recognition processing. Various styles, shapes, and sizes which are personal and different across individuals make the Arabic handwriting recognition process even harder. In this paper, the data used are Arabic handwritten images with 101 sample characters, each of which is written by 15 different handwritten characters (total sample 101x15) with the same size (81x81 pixels). A well-chosen feature is crucial for making good recognition results. In this study, the

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Wang, Kai, Jian-ming Jin, Guang-shun Shi, and Qing-ren Wang. "Chinese Font Recognition Based on Feature Point." Journal of Electronics & Information Technology 30, no. 2 (2011): 272–76. http://dx.doi.org/10.3724/sp.j.1146.2006.01129.

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Osman, Mohd Zamri, Mohd Aizaini Maarof, Mohd Foad Rohani, Nilam Nur Amir Sjarif, and Nor Saradatul Akmar Zulkifli. "A multi-color based features from facial images for automatic ethnicity identification model." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 3 (2020): 1383. http://dx.doi.org/10.11591/ijeecs.v18.i3.pp1383-1390.

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<span style="font-size: 9pt; font-family: 'Times New Roman', serif;">Ethnicity identification for demographic information has been studied for soft biometric analysis, and it is essential for human identification and verification. Ethnicity identification remains popular and receives attention in a recent year especially in automatic demographic information. Unfortunately, ethnicity identification technique using color-based feature mostly failed to determine the ethnicity classes accurately due to low properties of features in color-based. Thus, this paper purposely analyses the accurac

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Suñer, Avel·lina, and Angela Di Tullio. "Bare adjectives as syncretic forms." Borealis – An International Journal of Hispanic Linguistics 3, no. 1 (2014): 23. http://dx.doi.org/10.7557/1.3.1.2751.

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<span style="font-size: 11.0pt; mso-bidi-font-size: 12.0pt; line-height: 115%; font-family: Calibri; mso-ascii-theme-font: minor-latin; mso-fareast-font-family: 'ＭＳ明朝'; mso-fareast-theme-font: minor-fareast; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; mso-ansi-language: EN-GB; mso-fareast-language: ES; mso-bidi-language: AR-SA;" lang="EN-GB">The goal of this paper is to discuss the categorical <em style="mso-bidi-font-style: normal;">status</em> and semantic properties of the so-called <em style="mso-bidi-fo

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Ding, Liuxu, Yuefeng Liu, Qiyan Zhao, and Yunong Liu. "Text Font Correction and Alignment Method for Scene Text Recognition." Sensors 24, no. 24 (2024): 7917. https://doi.org/10.3390/s24247917.

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Text recognition is a rapidly evolving task with broad practical applications across multiple industries. However, due to the arbitrary-shape text arrangement, irregular text font, and unintended occlusion of font, this remains a challenging task. To handle images with arbitrary-shape text arrangement and irregular text font, we designed the Discriminative Standard Text Font (DSTF) and the Feature Alignment and Complementary Fusion (FACF). To address the unintended occlusion of font, we propose a Dual Attention Serial Module (DASM), which is integrated between residual modules to enhance the f

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Ali, Aree, and Bayan Omer. "Invarianceness for Character Recognition Using Geo-Discretization Features." Computer and Information Science 9, no. 2 (2016): 1. http://dx.doi.org/10.5539/cis.v9n2p1.

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<span style="font-size: 10pt; font-family: 'Times New Roman','serif'; mso-bidi-font-size: 11.0pt; mso-fareast-font-family: 宋体; mso-font-kerning: 1.0pt; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">Recognition rate of characters in the handwritten is still a big challenge for the research because of a shape variation, scale and format in a given handwritten character. A more complicated handwritten character recognition system needs a better feature extraction technique that deal with such variation of hand writing. In other hand, to obtai

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Li, Kangying, Biligsaikhan Batjargal, and Akira Maeda. "A Prototypical Network-Based Approach for Low-Resource Font Typeface Feature Extraction and Utilization." Data 6, no. 12 (2021): 134. http://dx.doi.org/10.3390/data6120134.

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This paper introduces a framework for retrieving low-resource font typeface databases by handwritten input. A new deep learning model structure based on metric learning is proposed to extract the features of a character typeface and predict the category of handwrittten input queries. Rather than using sufficient training data, we aim to utilize ancient character font typefaces with only one sample per category. Our research aims to achieve decent retrieval performances over more than 600 categories of handwritten characters automatically. We consider utilizing generic handcrafted features to t

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Batterink, Laura J., Larry Y. Cheng, and Ken A. Paller. "Neural Measures Reveal Implicit Learning during Language Processing." Journal of Cognitive Neuroscience 28, no. 10 (2016): 1636–49. http://dx.doi.org/10.1162/jocn_a_00985.

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Language input is highly variable; phonological, lexical, and syntactic features vary systematically across different speakers, geographic regions, and social contexts. Previous evidence shows that language users are sensitive to these contextual changes and that they can rapidly adapt to local regularities. For example, listeners quickly adjust to accented speech, facilitating comprehension. It has been proposed that this type of adaptation is a form of implicit learning. This study examined a similar type of adaptation, syntactic adaptation, to address two issues: (1) whether language compre

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Bao, Congwang, Yuan Li, and En Lu. "Design and Implementation of Dongba Character Font Style Transfer Model Based on AFGAN." Sensors 24, no. 11 (2024): 3424. http://dx.doi.org/10.3390/s24113424.

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Dongba characters are ancient ideographic scripts with abstract expressions that differ greatly from modern Chinese characters; directly applying existing methods cannot achieve the font style transfer of Dongba characters. This paper proposes an Attention-based Font style transfer Generative Adversarial Network (AFGAN) method. Based on the characteristics of Dongba character images, two core modules are set up in the proposed AFGAN, namely void constraint and font stroke constraint. In addition, in order to enhance the feature learning ability of the network and improve the style transfer eff

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Zhang, Likun, Xiaoyan Li, Yi Tang, Fangbin Song, Tian Xia, and Wei Wang. "Contemporary Advertising Text Art Design and Effect Evaluation by IoT Deep Learning under the Smart City." Security and Communication Networks 2022 (July 22, 2022): 1–14. http://dx.doi.org/10.1155/2022/5161398.

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This work intends to solve the problem that the current artistic typeface generation methods rely too much on manual intervention, lack novelty, and the single font local feature and the global feature extraction method cannot fully describe the font features. Firstly, it proposes a handwritten word recognition model based on generalized search trees (GIST) and the pyramid histogram of oriented gradient (PHOG). The local features and global features of the font are fused. Secondly, a model of automatic artistic typeface generation based on generative adversarial networks (GAN) is constructed,

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Muhaxov, Harhenbek, Zhong Lou, Wang Li, Tolewbek Samet, and Aheyeh Harhenbek. "Experimental Research on Signal Recognition Algorithm of Wireless Sensor Language." International Journal of Online Engineering (iJOE) 12, no. 10 (2016): 38. http://dx.doi.org/10.3991/ijoe.v12i10.6203.

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<p style="margin: 0in 0in 10pt;"><span style="-ms-layout-grid-mode: line;"><span style="font-family: Times New Roman; font-size: small;">In the past several decades, much research has been carried out on the </span><a name="OLE_LINK9"></a><span style="font-family: Times New Roman; font-size: small;">wireless</span><span style="font-family: Times New Roman; font-size: small;"> sensor network which is widely used in the fields of national defense and national economy within China. The main function of the language sensor is to transfer the vo

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Mohd Kadir, Nasibah Husna, Sharifah Nur Syafiqah Mohd Nur Hidayah, Norasiah Mohammad, and Zaidah Ibrahim. "Comparison of convolutional neural network and bag of features for multi-font digit recognition." Indonesian Journal of Electrical Engineering and Computer Science 15, no. 3 (2019): 1322. http://dx.doi.org/10.11591/ijeecs.v15.i3.pp1322-1328.

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<span>This paper evaluates the recognition performance of Convolutional Neural Network (CNN) and Bag of Features (BoF) for multiple font digit recognition. Font digit recognition is part of character recognition that is used to translate images from many document-input tasks such as handwritten, typewritten and printed text. BoF is a popular machine learning method while CNN is a popular deep learning method. Experiments were performed by applying BoF with Speeded-up Robust Feature (SURF) and Support Vector Machine (SVM) classifier and compared with CNN on Chars74K dataset. The recogniti

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Feiyu, Zhang, Yang Yi, Huang Weixing, Zhang Guigang, and Wang Jian. "Improving Font Effect Generation based on Pyramid Style Feature." International Journal of Performability Engineering 16, no. 8 (2020): 1271. http://dx.doi.org/10.23940/ijpe.20.08.p14.12711278.

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Waldron, John W. F., Rebecca A. Jamieson, Hayley D. Pothier, and Chris E. White. "Sedimentary and tectonic setting of a mass-transport slope deposit in the Halifax Group, Halifax Peninsula, Nova Scotia, Canada." Atlantic Geology 51, no. 1 (2015): 084. http://dx.doi.org/10.4138/atlgeol.2015.004.

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<p align="LEFT">Fine-grained metasedimentary rocks of the Halifax Group in southern mainland Nova Scotia can be subdivided into mappable units. In Halifax Peninsula, sulphide-rich hornfels, black slate, metasiltstone, and metasandstone of the Cunard Formation are overlain by grey metasedimentary rocks with abundant cross-laminations and local carbonate and calc-silicate concretions, assigned to the Bluestone Quarry Formation. No fossils are known from the Bluestone Quarry Formation but lithological correlatives elsewhere are Tremadocian. The Bluestone Quarry Formation is here divided int

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Kurniawan, Dede. "ANALISIS SEMIOTIKA TIPOGRAFI: EKSISTENSI HELVETICA DALAM KARYA DESAIN." JURNAL Dasarrupa: Desain dan Seni Rupa 4, no. 2 (2022): 43–50. http://dx.doi.org/10.52005/dasarrupa.v4i2.132.

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This study attempts to explore the existence of the Helvetica font in several design works by borrowing the typographical semiotic perspective offered by Theo van Leeuwen. This study applies qualitative research methods by collecting data from observations, interviews and documentation. The results show that the Helvetica font still exists in design works because of its neutral, neutral character in the sense of not taking sides in any of its meanings, for example only thin which can be interpreted as exclusive, luxurious or black which is interpreted as bold, arrogant. because Helvetica weigh

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Nasrollahi, Samira, and Afshin Ebrahimi. "Printed Persian Subword Recognition Using Wavelet Packet Descriptors." Journal of Engineering 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/465469.

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In this paper, we present a new approach to offline OCR (optical character recognition) for printed Persian subwords using wavelet packet transform. The proposed algorithm is used to extract font invariant and size invariant features from 87804 subwords of 4 fonts and 3 sizes. The feature vectors are compressed using PCA. The obtained feature vectors yield a pictorial dictionary for which an entry is the mean of each group that consists of the same subword with 4 fonts in 3 sizes. The sets of these features are congregated by combining them with the dot features for the recognition of printed

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Sheppard, Shannon M., Susanne L. Nobles, Anton Palma, et al. "One Font Doesn’t Fit All: The Influence of Digital Text Personalization on Comprehension in Child and Adolescent Readers." Education Sciences 13, no. 9 (2023): 864. http://dx.doi.org/10.3390/educsci13090864.

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Reading comprehension is an essential skill. It is unclear whether and to what degree typography and font personalization may impact reading comprehension in younger readers. With advancements in technology, it is now feasible to personalize digital reading formats in general technology tools, but this feature is not yet available for many educational tools. The current study aimed to investigate the effect of character width and inter-letter spacing on reading speed and comprehension. We enrolled 94 children (kindergarten–8th grade) and compared performance with six font variations on a word-

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Alexeeva, Svetlana, Vladislav Zubov, and Alena Konina. "Adolescents reading texts in LexiaD, a dyslexia-specific Cyrillic font: A mobile eye-tracking study." Russian Journal of Cognitive Science 9, no. 1-2 (2022): 65–82. http://dx.doi.org/10.47010/22.1-2.5.

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Recently, LexiaD, a dyslexia-specific Cyrillic font, was tested alongside the widely used Arial font in an experiment during which adolescents with and without dyslexia silently read sentences on a computer screen (Alexeeva et al., 2022). LexiaD showed a worse performance than Arial at the beginning of the experiment, but by the end of it, LexiaD demonstrated a positive effect in feature extraction and similar performance in lexical access, text integration, and global reading processing. We suggest that Arial’s initial advantage can be explained either by its familiarity or by its design feat

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Lundquist, Björn. "Noun-verb conversion without a generative lexicon." Nordlyd 36, no. 1 (2009): pp. http://dx.doi.org/10.7557/12.221.

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<!--[if gte mso 10]> <mce:style><! /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Vanlig tabell"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} > <! [endif] > <p class="MsoNormal"><span lang="EN-US">This paper discusses diﬀerent types of zero-derived

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Stein, Timo, Jan Zwickel, Maria Kitzmantel, Johanna Ritter, and Werner X. Schneider. "Irrelevant Words Trigger an Attentional Blink." Experimental Psychology 57, no. 4 (2010): 301–7. http://dx.doi.org/10.1027/1618-3169/a000035.

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It has been argued that salient distractor items displayed during rapid serial visual presentation (RSVP) trigger an attentional blink (AB) when they share features with the target item. Here we demonstrate that salient distractor words induce an AB independently of feature overlap with the target. In two experiments a color-highlighted irrelevant word preceded a target by a variable lag in an RSVP series of false font strings. Target identification was reduced at short relative to long temporal lags between the distractor word and the target, irrespective of feature sharing with the distracto

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Shaina*, Harpreet Kaur Bajaj. "Analysis of Proposed Technique for Graphical Representation of Isolated Character Using SVM Classifier." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 11 (2016): 422–29. https://doi.org/10.5281/zenodo.167158.

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A graphical representation is a visual display of data and statistical results. It is more often and effective than presenting data in tabular form. Optical Character Recognition (OCR) requires a graphical representation of text to interpret, which usually comes from a scanned image. Support Vector Machine (SVM) describes the concept that how the decision planes are made which helps in defining the decision boundaries. In this paper a method of isolated graphical representation has been proposed using SVM Classifier. The performance is measured in the terms of accuracy using different font sty

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Satyanarayana, Y. V. V., U. Ravi Babu, and S. Maruthu Permal. "Printed Telugu Numeral Recognition based on Structural, Skeleton and Water Reservoir Features." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 10, no. 7 (2013): 1815–24. http://dx.doi.org/10.24297/ijct.v10i7.7042.

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Selection of feature extraction method is most important factor in achieving high recognition performance in automatic numeral recognition systems In this paper, a new proposed system for Telugu printed numeral characters recognition using number of contours, skeleton feature, water reservoir features, and ratio of length of Top line to bottom line of the image. Printed Telugu numerals are scan converted to binary images and extract the features irrespective of size of the image. The proposed method is applied with success to a database of 3150 printed multi-font printed Telugu numerals The re

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Mengistu, Abrham Debasu, and Dagnachew Melesew Alemayehu. "Speech Processing for Text Independent Amharic Language Dialect Recognition." Indonesian Journal of Electrical Engineering and Computer Science 5, no. 1 (2017): 115. http://dx.doi.org/10.11591/ijeecs.v5.i1.pp115-122.

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<span style="color: #666666; font-family: Verdana, Arial, Helvetica, sans-serif; font-size: 11.2px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: 2; text-align: left; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: #ffffff; display: inline !important; float: none;">Dialect is a difference of verbal communication spoken by people from a particular society or geographic area so the paper focuses on Amharic langua

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Alghifari, Muhammad Fahreza, Teddy Surya Gunawan, and Mira Kartiwi. "Speech Emotion Recognition Using Deep Feedforward Neural Network." Indonesian Journal of Electrical Engineering and Computer Science 10, no. 2 (2018): 554. http://dx.doi.org/10.11591/ijeecs.v10.i2.pp554-561.

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Speech emotion recognition (SER) is currently a research hotspot due to its challenging nature but bountiful future prospects. The objective of this research is to utilize Deep Neural Networks (DNNs) to recognize human speech emotion. First, the chosen speech feature Mel-frequency cepstral coefficient (MFCC) were extracted from raw audio data. Second, the speech features extracted were fed into the DNN to train the network. The trained network was then tested onto a set of labelled emotion speech audio and the recognition rate was evaluated. Based on the accuracy rate the MFCC, number of neuro

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Ariwibowo, Vincentius Seto. "Stylistics Analysis Of National Geographic Magazine’s Cover June Edition." Jurnal DinamikA 2, no. 2 (2021): 33–46. http://dx.doi.org/10.18326/dinamika.v2i2.33-46.

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This research presented the Stylistics analysis of National Geographic magazine’s cover June edition. The magazine was chosen because it is one of the magazine's newest issues by the time the researcher conducting this research. The Stylistic approach was employed to understand and reveal the magazine editor's purposes in using specific language and visual features. Considering this research analyzes visual feature; therefore, the theory of visual grammar was employed. To achieve the analysis's goal, the researcher analyzed the language features from three language levels and a feature from vi

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Liu, Yitian, and Zhouhui Lian. "DeepCalliFont: Few-Shot Chinese Calligraphy Font Synthesis by Integrating Dual-Modality Generative Models." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 4 (2024): 3774–82. http://dx.doi.org/10.1609/aaai.v38i4.28168.

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Few-shot font generation, especially for Chinese calligraphy fonts, is a challenging and ongoing problem. With the help of prior knowledge that is mainly based on glyph consistency assumptions, some recently proposed methods can synthesize high-quality Chinese glyph images. However, glyphs in calligraphy font styles often do not meet these assumptions. To address this problem, we propose a novel model, DeepCalliFont, for few-shot Chinese calligraphy font synthesis by integrating dual-modality generative models. Specifically, the proposed model consists of image synthesis and sequence generatio

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Wang, Xijuan. "A Human Body Gait Recognition System Based on Fourier Transform and Quartile Difference Extraction." International Journal of Online Engineering (iJOE) 13, no. 07 (2017): 129. http://dx.doi.org/10.3991/ijoe.v13i07.7294.

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<span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-fareast-font-family: 'Times New Roman'; mso-fareast-language: DE; mso-bidi-font-weight: bold; mso-ansi-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-US">A research method of gait recognition based on feature combination</span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-fareast-font-family: 宋体; mso-fareast-language: ZH-CN; mso-bidi-font-weight: bold; mso-ansi-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-US"> is proposed, which includes the wavelet transform (W

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Chen, Chung-Hsing, and Ko-Wei Huang. "Lightweight CNN Architecture for IoT: Enhancing Character Recognition in Multiple Fonts." Journal of Internet Technology 25, no. 7 (2024): 987–96. https://doi.org/10.70003/160792642024122507004.

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Existing approaches to English character recognition generally ignore font differences, and those based on deep learning are often trained on only one font owing to computational constraints. To address this problem, we propose the Very Lightweight Network (VLNet), a lightweight convolutional neural network. First, we decompose the characters of a given font into their constituent strokes. Subsequently, we pass the stroke information as input to a simple convolutional neural network. Stroke-based feature extraction reduces the requirement for graphics data and training input size. The network

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Abdegadir Khalifa, Mahmoud, Ammar Mohammed Ali, Saif Ali Alsadai, Liying Zheng, Nahla Fadel Alwan, and Gadiaa Saeed Mahdi. "A Novel Arabic Words Recognition System Using Hyperplane Classifier." Wasit Journal of Computer and Mathematics Science 1, no. 2 (2022): 12–20. http://dx.doi.org/10.31185/wjcm.vol1.iss2.45.

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Topic of exhaustive study for about past decades has been carried out in machine imitation of human reading. a small number of investigates have been accepted on the detection of cursive font writing like Arabic texts for its individual challenge and difficulty .In this work, a novel technique for automatic Arabic font recognition is proposed to demonstrate an suitable recognition rate for multi fonts styles and multi sizes of Arabic word images. The scheme can be classified into a number of steps. First, segmenting Arabic line into words depending on the vertical projection and dynamic

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Hou, Liqun, Junteng Hao, Yongguang Ma, and Neil Bergmann. "IWSNs with On-Sensor Data Processing for Energy Efficient Machine Fault Diagnosis." International Journal of Online and Biomedical Engineering (iJOE) 15, no. 08 (2019): 42. http://dx.doi.org/10.3991/ijoe.v15i08.10314.

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<span style="color: black; font-family: 'Times New Roman','serif'; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-themecolor: text1; mso-ansi-language: EN-US; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US">Machine fault diagnosis systems need to collect and transmit dynamic signals, like vibration and current, at high-speed. However, industrial wireless sensor networks (IWSNs) and Industrial Internet of Things (IIoT) are generally based on low-speed wireless protocols, such as ZigBee and IEEE802.15.4. Large amounts of transmission data will </span&

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Wang, Yiwen, Hornisa Mamat, Xuebin Xu, Alimjan Aysa, and Kurban Ubul. "Scene Uyghur Text Detection Based on Fine-Grained Feature Representation." Sensors 22, no. 12 (2022): 4372. http://dx.doi.org/10.3390/s22124372.

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Scene text detection task aims to precisely localize text in natural environments. At present, the application scenarios of text detection topics have gradually shifted from plain document text to more complex natural scenarios. Objects with similar texture and text morphology in the complex background noise of natural scene images are prone to false recall and difficult to detect multi-scale texts, a multi-directional scene Uyghur text detection model based on fine-grained feature representation and spatial feature fusion is proposed, and feature extraction and feature fusion are improved to

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Mohammed, Aveen J., and Hasan S. M. Al-Khaffaf. "Font Recognition of English Letters Based on Distance Profile Features." Science Journal of University of Zakho 8, no. 2 (2020): 66–71. http://dx.doi.org/10.25271/sjuoz.2020.8.2.694.

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This paper presents a system for recognizing English fonts from character images. The distance profile is the feature of choice used in this paper. The system extracts a vector of 106 features and feeds it into a support vector machine (SVM) classifier with a radial basis function (RBF) kernel. The experiment is divided into three phases. In the first phase, the system trains the SVM with different Gamma and C parameters. In the second phase, the validation phase, we validate and select the pair of Gamma and C values that yield the best recognition rates. In the final phase, the testing phase,

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Jan, Z., M. Shabir, M. A. Khan, A. Ali, and M. Muzammal. "Online Urdu Handwriting Recognition System Using Geometric Invariant Features." Nucleus 53, no. 2 (2016): 89–98. https://doi.org/10.71330/thenucleus.2016.216.

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Online touch sensitive devices facilitate users by providing an easy way for inputting online handwritten text. Many useful applications are developed for other cursive script language and are practically used in different fields like banking, commerce, academics, administration and education etc. There are also some systems proposed for online Urdu handwriting recognition but either they have low accuracy rates or high constraints on user while writing. Online Urdu handwriting recognition is a difficult task due to its cursive property and writing complexity. The proposed system tries to reco

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Bataineh, Bilal, Siti Norul Huda Sheikh Abdullah, and Khairuddin Omar. "A novel statistical feature extraction method for textual images: Optical font recognition." Expert Systems with Applications 39, no. 5 (2012): 5470–77. http://dx.doi.org/10.1016/j.eswa.2011.11.078.

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BS, Ujwala, and Ujwala K. "A REVIEW PAPER ON OCR USING CONVOLUTIONAL NEURAL NETWORKS." International Journal of Engineering Applied Sciences and Technology 7, no. 7 (2022): 102–6. http://dx.doi.org/10.33564/ijeast.2022.v07i07.018.

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this paper presents a literature review on OCR for different languages using convolutional neural network techniques. Optical Character Recognition is the process of converting an input text image into a machine encoded format. Different methods are used in OCR for different languages. The main steps of optical character recognition are pre-processing, segmentation and recognition. Recognizing handwritten text is harder than recognizing printed text. Convolutional Neural Network has shown remarkable improvement in recognizing characters of different languages. The novelty of the OCR is its rob

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Yao, Yong, Wei Hua Wang, Dong Fang Zhang, and Hong Yan Guo. "Printed Character Database Analysis Based Printed Document Examination." Applied Mechanics and Materials 411-414 (September 2013): 1260–66. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.1260.

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This paper presented a study on printed character database image analysis based printed document examination in purpose of identifying the printer which created a suspect printed document. It was composed of printed document image acquisition, image pre-processing, feature extraction and classifier. After characters are extracted and recognized in pre-processing, stroke feature sequence of each text block are calculated, and the HU moments of the sequence are also calculated. Finally, the Euclid distance classifier and MQDF classifier are used to recognize the fonts using the above two kind of

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Dobrolubsky, Andrey, Nadia Ieksarova, and Vladimir Yeksarov. "Smart port city of Odessa: brilliant embodiment of Vitruvius` theories of beauty." VITRUVIO - International Journal of Architectural Technology and Sustainability 1, no. 1 (2016): 1. http://dx.doi.org/10.4995/vitruvio-ijats.2016.5157.

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<p align="JUSTIFY"><span style="color: #000000;"><span style="font-family: 'Times New Roman', serif;"><span style="font-size: small;"><span lang="en-US">The condition of successive</span></span></span></span><span style="color: #000000;"><span style="font-family: 'Times New Roman', serif;"><span style="font-size: small;"><span lang="en-US">development, sustainability of the whole is a continuous relation between the present, the past and the future. An interdisciplinary approach aimed to create the holistic picture o

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Jaiem, Faten Kallel, and Monji Kherallah. "A novel Arabic font recognition system based on texture feature and dynamic training." International Journal of Intelligent Systems Technologies and Applications 16, no. 4 (2017): 289. http://dx.doi.org/10.1504/ijista.2017.088053.

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Jaiem, Faten Kallel, and Monji Kherallah. "A novel Arabic font recognition system based on texture feature and dynamic training." International Journal of Intelligent Systems Technologies and Applications 16, no. 4 (2017): 289. http://dx.doi.org/10.1504/ijista.2017.10008858.

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Davy, Zowie, Sarah Amsler, and Karen Duncombe. "Facilitating LGBT Medical, Health and Social Care Content in Higher Education Teaching." Qualitative Research in Education 4, no. 2 (2015): 134. http://dx.doi.org/10.17583/qre.2015.1210.

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<span style="font-size: 9.0pt; line-height: 115%; font-family: 'Calibri','sans-serif'; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'Times New Roman'; mso-ansi-language: ES; mso-fareast-language: ES; mso-bidi-language: AR-SA;">Increasingly, Lesbian, Gay, Bisexual, and Transgender (LGBT) health care is becoming an important quality assurance feature of primary, secondary and tertiary healthcare in Britain. While acknowledging these very positive developments, teaching LGBT curricula content is contingent upon having educators understand the complexity of LGBT lives. T

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Sambyal, Nitigya, and Pawanesh Abrol. "Feature based Text Extraction System using Connected Component Method." International Journal of Synthetic Emotions 7, no. 1 (2016): 41–57. http://dx.doi.org/10.4018/ijse.2016010104.

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Text detection and segmentation system serves as important method for document analysis as it helps in many content based image analysis tasks. This research paper proposes a connected component technique for text extraction and character segmentation using maximally stable extremal regions (MSERs) for text line formation followed by connected components to determined separate characters. The system uses a cluster size of five which is selected by experimental evaluation for identifying characters. Sobel edge detector is used as it reduces the execution time but at the same time maintains qual

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BOUSLAMA, FAOUZI. "NEURAL NETWORKS IN THE RECOGNITION OF MACHINE PRINTED ARABIC CHARACTERS." International Journal of Pattern Recognition and Artificial Intelligence 13, no. 03 (1999): 395–414. http://dx.doi.org/10.1142/s0218001499000239.

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The objective of this study is to analyze and compare three different recognition approaches to machine printed Arabic characters. The first approach is a template matching and a correlation technique where an input character is compared to a standard set of stored prototype images. The second and the third approaches are based on feature analysis and matching. The features in the second approach are extracted from the horizontal and vertical projections of the images of characters. The third approach is a structural approach where the features are extracted from the geometry of the segments t

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Li, Yuxia, and Zhinan Zhou. "RFID Anti-Collision Detection Algorithm Based on Improved Adaptive N-Tree." International Journal of Online Engineering (iJOE) 14, no. 10 (2018): 129. http://dx.doi.org/10.3991/ijoe.v14i10.9310.

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<p style="margin: 1em 0px;"><span style="font-family: Times New Roman; font-size: medium;">This paper proposes a type of improved adaptive N-tree anti-collision algorithm based on the traditional one for RFID system by combination with maximum likelihood estimation and probe pre-detection. This algorithm inherits some features from Alpha- and tree-based anti-collision algorithms and effectively restrain the star-vation of the two algorithms. It has also filled in the gaps of tag collision with higher probability. The study turns out that the improved adaptive N-tree anti-collision

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Harmadani, Dwindy, Josephine Sudiman, Sukartini, and Reno Fithri Meuthia. "Relevansi Fungsi dan Formula di Microsoft Excel Pada Tenaga Kerja Akuntan." Akuntansi dan Manajemen 17, no. 2 (2022): 28–40. http://dx.doi.org/10.30630/jam.v17i2.189.

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This study aims to determine the relevance of functions and formulas in Microsoft Excel on jobs related to accounting. This type of research is descriptive analytic qualitative research. The data collection method of this research is interviews. This study focuses on graduates of the Accounting Department who work in public accounting firms and in companies and often use Microsoft Excel in doing their work. The data analysis technique used is an interactive model analysis technique. Testing the validity of the data in this study includes the credibility test, transferability test, dependence t

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FatanehAlavipour and Broumandnia Ali. "PERSIAN CHARACTER RECOGNITION USING NEW HYBRIDIZATION OF INDEPENDENT ORTHOGONAL MOMENTS." International Journal of Computational Science and Information Technology (IJCSITY) 2, May (2014): 1–10. https://doi.org/10.5281/zenodo.3472295.

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<strong>ABSTRACT </strong> Character recognition is a new research field in the domain of pattern recognition which deals with the style of writing. Some of the challengeable problems in character identification are changing in the style of writing, font and turns of words and etc. In this paper, the goal is Persian character identification using independent orthogonal moment as the feature extraction technique.The proposed feature extraction method is the combination of Pseudo-Zernike Moment and Fourier-Mellin Moment called Pseudo-ZernikeMellin Moment to extract feature vector from Persian ch

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Hilola, Mardieva, and Melixolova Nilufar. "SPECIAL FEATURE OF WORD CREATION." JOURNAL OF SCIENCE-INNOVATIVE RESEARCH IN UZBEKISTAN 2, no. 2 (2024): 6–8. https://doi.org/10.5281/zenodo.10609240.

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