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Littérature scientifique sur le sujet « Rocessing handwriting data effectively »

Auteur : Grafiati
Publié le 7 juin 2025
Mis à jour le 2 août 2025

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Articles de revues sur le sujet "Rocessing handwriting data effectively"

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Gaurav, Pratap Singh Chauhun* Suman Rani. "An Overview of the 3-IN-1 TEXT TOOLS And Its Application." International Journal of Scientific Research and Technology 2, no. 5 (2025): 195–207. https://doi.org/10.5281/zenodo.15363797.

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Handwriting apps have revolutionized how users interact with devices, enabling the capture and recognition of handwritten input. This project focuses on designing and developinga Handwriting App using React JS for both the frontendand backend, leveragingits versatilityand performance to create a seamless user experience.  Existing solution softenrely on either platform-specific applicationsorthird-partyservices,whichcan be limited in functionality and costly. Many of these fail to provide an integrated environment for capturing, storing, and processing handwriting data effectively. Our pr
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Ren, Qing-Dao-Er-Ji, Lele Wang, Zerui Ma, and Saheya Barintag. "Offline Mongolian Handwriting Recognition Based on Data Augmentation and Improved ECA-Net." Electronics 13, no. 5 (2024): 835. http://dx.doi.org/10.3390/electronics13050835.

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Writing is an important carrier of cultural inheritance, and the digitization of handwritten texts is an effective means to protect national culture. Compared to Chinese and English handwriting recognition, the research on Mongolian handwriting recognition started relatively late and achieved few results due to the characteristics of the script itself and the lack of corpus. First, according to the characteristics of Mongolian handwritten characters, the random erasing data augmentation algorithm was modified, and a dual data augmentation (DDA) algorithm was proposed by combining the improved
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Rogushina, J. V., and A. Ya Gladun. "Application of ontological analysis for metadata processing in the interpretation of BIG DATA at the semantic level." PROBLEMS IN PROGRAMMING, no. 4 (December 2020): 055–70. http://dx.doi.org/10.15407/pp2020.04.055.

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The paper considers the main aspects of modern technologies applied for knowledge analysis to obtain information from Big Data. The analysis of the current state of research in this area shows that background knowledge subject areas of user interest represented by domain ontologies can be used both in order to effectively analysis of information acquried from certain sets of Big Data, and to make this acquisition more useful. With the help of such ontologies, users can formally describe the scope of their information needs, define the structure of the required information objects and explicitl
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Zhao, Zhenshen, and Tiancai Zhou. "High-Performance Roaming Display Algorithm for Ultra-Large Screen Handwriting." Journal of Computing and Electronic Information Management 14, no. 2 (2024): 1–3. https://doi.org/10.54097/m0df9s31.

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With the rapid development of smart education, the application of smart chalkboard software in teaching is becoming increasingly widespread. This article proposes a high-performance roaming display algorithm aimed at improving the smoothness and response speed of handwriting input on large screens. This algorithm achieves efficient handwriting input and real-time display through techniques such as data collection and preprocessing, dynamic partitioning and caching mechanisms, parallel computing and multi-threaded processing, as well as intelligent prediction and optimization. The experimental
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Chang, Chia-Hsiu, Yuan-Hsiung Tsai, and Hung-Cheng Tai. "Development and evaluation of an EMP course to teach fMRI technology and brain science in handwriting for university nursing students." Research and Practice in Technology Enhanced Learning 20 (September 25, 2024): 029. http://dx.doi.org/10.58459/rptel.2025.20029.

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In traditional nursing education, brain science is often limited to physiology, anatomy, and pathology, with little emphasis on advanced diagnostic tools like fMRI or the brain’s functional processes, such as language learning and handwriting. This study developed an English for Medical Purposes (EMP) course to teach university nursing students about fMRI technology and brain science related to handwriting, highlighting the importance of interprofessional education. The study aimed to (a) assess the course’s effectiveness in enhancing students’ knowledge in fMRI, brain science, and handwriting
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Pratiwi, Dian, Syaifudin Syaifudin, Ahmad Fauzy, and Mohammad Khasan. "Personality Type Analysis through Handwriting Characteristics Mapping using Invariant Moment Descriptors." Register 9, no. 2 (2023): 103–11. http://dx.doi.org/10.26594/register.v9i2.3420.

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Handwriting patterns are unique to each individual and can offer valuable insights into their mental health conditions, personality traits, behavioral tendencies, mindsets, and more. To effectively analyze someone's personality or solve a problem using their handwriting, it is crucial to employ suitable descriptors that accurately represent the essential information it contains. Therefore, this study aims to explore the application of invariant moments as descriptors to map personality types using the psychological technique of enneagrams in conjunction with handwriting patterns. The main proc
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Wang, S. H., S. Q. Lyu, M. L. Hou, Z. H. Gao, and M. Huang. "SURFACE HANDWRITING ENHANCEMENT OF ARTIFACTS BASED ON MANIFOLD LEARNING AND MIXED PIXEL DECOMPOSITION." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2022 (May 30, 2022): 917–22. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2022-917-2022.

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Abstract. Written information on the surface of cultural relics can record important historical events. Due to the influence of natural and human factors, the surface of cultural relics fades and the words are difficult to identify. Take advantage of the hyperspectral data image and spectral unity and wide spectral range, a cultural relics surface handwriting enhancement method based on manifold learning and mixed pixel decomposition was proposed. First, the minimum noise fraction (MNF) transformation was carried out on the hyperspectral image, and then the top 10 bands were selected for inver
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Effendi, Edi Arif, Favorisen Rosyking Lumbanraja, Akmal Junaidi, and Admi Syarif. "Implementasi Metode Deep Learning Untuk Klasifikasi Gambar Tulisan Tangan." Jurnal Pepadun 4, no. 2 (2023): 100–106. http://dx.doi.org/10.23960/pepadun.v4i2.166.

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The advancement of current technology has led to the widespread utilization of pattern recognition in diverse fields, such as identifying signature patterns, fingerprints, faces, and handwriting. Human handwriting exhibits variations from one person to another, often making it challenging to read or recognize, which can hinder daily activities, particularly in transactions requiring handwritten input. Handwriting, being a distinct expression of individuals, can be effectively distinguished or recognized using pattern recognition methods, particularly through computer-based classification techn
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Singh, Puja. "General Characteristics of Handwriting and its Psychological Importance." Cognizance Journal of Multidisciplinary Studies 2, no. 2 (2022): 1–4. http://dx.doi.org/10.47760/cognizance.2022.v02i02.001.

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Each educated human have their own novel penmanship qualities which is normally inserted. Penmanship is the photo of the inner struggles continuing. The review shows that the penmanship appraisals can fill in as a viable indicator for the guess of the previously mentioned aggravations and perhaps some others too. The proficient finding of the aggravations in the area of brain science is mostly founded on indications referenced in books of analytic rule that are generally physical and mental yet semantic capacities like penmanship can likewise be utilized for something similar. It very well may
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Puja, Singh. "General Characteristics of Handwriting and its Psychological Importance." Cognizance Journal of Multidisciplinary Studies 2, no. 2 (2022): 1–4. https://doi.org/10.47760/cognizance.2022.v02i02.001.

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Each educated human have their own novel penmanship qualities which is normally inserted. Penmanship is the photo of the inner struggles continuing. The review shows that the penmanship appraisals can fill in as a viable indicator for the guess of the previously mentioned aggravations and perhaps some others too. The proficient finding of the aggravations in the area of brain science is mostly founded on indications referenced in books of analytic rule that are generally physical and mental yet semantic capacities like penmanship can likewise be utilized for something similar. It very well may
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Chapitres de livres sur le sujet "Rocessing handwriting data effectively"

1

Du, Panpan, and Yan Li. "Handwritten English Character Recognition Method Based on Deep Learning." In Advances in Transdisciplinary Engineering. IOS Press, 2024. http://dx.doi.org/10.3233/atde231286.

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In order to solve the problem of low accuracy of computer intelligent recognition of handwritten English in practical application, a method of font feature extraction and recognition using deep learning is proposed. Considering the serious differences of off-line handwriting styles of different people, the scheme uses the preprocessed image data to train the improved CNN model, reduces the interdependence of parameters. Then the improved LeNet-5 model is applied to the research of handwritten numeral recognition. The simulation results show that our method can effectively realize the automatic
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