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Статті в журналах з теми "Principles of segmentation"

Автор: Grafiati

Опубліковано: 28 травня 2022

Оновлено: 31 липня 2025

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1

Skarnitzl, Radek, and Pavel Machač. "Principles of Phonetic Segmentation." Phonetica 68, no. 3 (2011): 198–99. http://dx.doi.org/10.1159/000331902.

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2

Greengrove, Kathryn. "Needs-Based Segmentation: Principles and Practice." International Journal of Market Research 44, no. 4 (2002): 1–16. http://dx.doi.org/10.1177/147078530204400402.

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Анотація:

While the principles of needs or benefit-based market segmentation have been long established, its potential value as a route to a stronger market understanding and ultimately competitive advantage has been largely untapped in pharmaceutical marketing research, with internal process rather than market focus driving market understanding. Many of the tensions around the use of geodemographics for market segmentation in the consumer work are mirrored in the use of classification systems and diagnosis in the pharmaceutical environment. This paper presents the application of needs-based segmentatio

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3

Goryushkina, N. E., T. V. Gaifutdinova, E. V. Logvina, A. G. Redkin, V. V. Kudryavtsev, and Y. N. Shol. "Basic Principles of Tourist Services Market Segmentation." International Journal of Economics and Business Administration VII, Issue 2 (2019): 139–50. http://dx.doi.org/10.35808/ijeba/222.

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4

Garami, Linda, and József Fiser. "Temporal segmentation principles in vision and audition." Journal of Vision 24, no. 10 (2024): 1117. http://dx.doi.org/10.1167/jov.24.10.1117.

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5

Kulawik, Adam. "Principle of the Verse Segmentation." Annales Universitatis Paedagogicae Cracoviensis. Studia Poetica 12 (December 23, 2024): 421–57. https://doi.org/10.24917/23534583.12.25.

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This article is a translation of a part of a collective book published in 1984, which forms the foundations of the prosodic theory of verse, an original research project that was further developed into an independent theory of verse in several books. The paper explores the theoretical framework and principles underlying the segmentation of verse, distinguishing it from prose, argues that traditional verse theory has struggled to define and analyze verse effectively due to its reliance on metrics. The author proposes a redefinition of verse, emphasizing the role of prosodic segmentation, and ve

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6

Torkki, Paulus, Riikka-Leena Leskelä, Pirjo Mustonen, Miika Linna, and Paul Lillrank. "How to extend value-based healthcare to population-based healthcare systems? Defining an outcome-based segmentation model for health authority." BMJ Open 13, no. 11 (2023): e077250. http://dx.doi.org/10.1136/bmjopen-2023-077250.

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Анотація:

ObjectivesValue-based healthcare (VBHC) is considered the most promising guiding principle for a new generation of health service production. Many countries have attempted to apply VBHC to managerial and clinical decision-making. However, implementation remains in its infancy and varies between countries. The objective of the study is to help health systems implement a value-based approach by building an outcome-based population segmentation model for health authorities (HAs).DesignFirst, we define the principles according to which segmentation models in healthcare could be developed. Second,

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7

Kaushal, Rajesh Kumar, Naveen Kumar, Surya Narayan Panda, Priyanka Datta, and Jyoti Sharma. "Improving Learning Outcome with Segmentation and Cueing." Journal of Engineering Education Transformations 35, no. 1 (2021): 60–65. http://dx.doi.org/10.16920/jeet/2021/v35i1/22057.

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Abstract : The computer animations certainly help in deeply understanding the complex concepts. Moreover, computer animations are broadly used for nearly all subject disciplines. Some past studies highlighted that comprehension can be improved by deploying effective design principles within the computer animations. Thus, this study is aimed at finding the effectiveness of design principles particularly when segmentation and cueing design principles are served together within computer animations. A quantitative experimental study was designed and conducted. A total of 56 students willingly part

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8

HAVRYLKO, P. P., T. V. HUSHTAN, and K. Yu. SIMEKH. "Peculiarities of the application of the model for determining potential sales zones in the company's product sales system." Market Relations Development in Ukraine №3(262)2023 111 (May 23, 2023): 49–54. https://doi.org/10.5281/zenodo.7963933.

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The subject of the study is the application of the model for determining potential sales zones in the company’s product sales system. The purpose of the study is to determine the principles and factors of market segmentation of the company’s products. Research methods. The work uses the dialectical method of scientific knowledge, the method of analysis and synthesis, the comparative method, and the method of summarizing data. Work results. The paper defines the main principles of market segmentation of the company’s products. Factors taken into account when building a potenti

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9

Al Shehhi, Rasha, Prashanth Reddy Marpu, and Wei Lee Woon. "An Automatic Cognitive Graph-Based Segmentation for Detection of Blood Vessels in Retinal Images." Mathematical Problems in Engineering 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/7906165.

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This paper presents a hierarchical graph-based segmentation for blood vessel detection in digital retinal images. This segmentation employs some of perceptual Gestalt principles: similarity, closure, continuity, and proximity to merge segments into coherent connected vessel-like patterns. The integration of Gestalt principles is based on object-based features (e.g., color and black top-hat (BTH) morphology and context) and graph-analysis algorithms (e.g., Dijkstra path). The segmentation framework consists of two main steps: preprocessing and multiscale graph-based segmentation. Preprocessing

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10

Rozhko, Viktor. "Justification of consumer market segmentation as a mandatory tool of strategic marketing." Technology audit and production reserves 2, no. 4(70) (2023): 15–19. http://dx.doi.org/10.15587/2706-5448.2023.277373.

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Анотація:

The object of research is the theoretical aspects of consumer market segmentation and its role in strategic marketing. Ukrainian enterprises try to use and carry out various measures to increase the competitiveness of products, actively using methods of internal planning and management based on the principles of strategic marketing. One of the tools for developing a marketing plan in strategic marketing is segmentation. However, the content of strategic marketing is debatable; there is no unambiguous comprehensive approach, according to which consumer market segmentation is carried out. Thus,

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11

Zhu, Shan-shan, and Nelson H. C. Yung. "Sub-scene segmentation using constraints based on Gestalt principles." Journal of Visual Communication and Image Representation 25, no. 5 (2014): 994–1005. http://dx.doi.org/10.1016/j.jvcir.2014.02.017.

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12

Mkrtchian, Oleksandr. "Automatic landscape-ecological regionalization by the application of clustering and segmentation." Visnyk of the Lviv University. Series Geography, no. 47 (November 27, 2014): 177–84. http://dx.doi.org/10.30970/vgg.2014.47.950.

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The paper deals with the principles and methods of automatic landscape-ecological regionalization by the clusterization and segmentation methods. The employment of ecological morphometric indices as criteria for clusterization and segmentation has been justified. The method of the quantification of spatial dependencies between typological and regional spatial units based on information theory has been suggested. Key words: regionalization, clusterization, segmentation.

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13

Wang, Liang, and Kan Ren. "Attention-Based Mask R-CNN Enhancement for Infrared Image Target Segmentation." Symmetry 17, no. 7 (2025): 1099. https://doi.org/10.3390/sym17071099.

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Анотація:

Image segmentation is an important method in the field of image processing, while infrared (IR) image segmentation is one of the challenges in this field due to the unique characteristics of IR data. Infrared imaging utilizes the infrared radiation emitted by objects to produce images, which can supplement the performance of visible-light images under adverse lighting conditions to some extent. However, the low spatial resolution and limited texture details in IR images hinder the achievement of high-precision segmentation. To address these issues, an attention mechanism based on symmetrical c

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14

Li, Nan. "Medical Image Segmentation Research Status and Development Trends." Highlights in Science, Engineering and Technology 65 (August 29, 2023): 188–98. http://dx.doi.org/10.54097/hset.v65i.11459.

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As one of the important steps in medical image processing, medical image segmentation plays a pivotal role in clinical surgery and is widely used in application scenarios such as preoperative diagnosis, intraoperative navigation, and postoperative evaluation. In this paper, medical image segmentation technology is studied, and a variety of medical image segmentation methods are categorized and compared in an attempt to explore the development law of medical image segmentation technology. Firstly, the medical image segmentation technology is classified and studied according to its different met

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15

Yu, Ying, Chunping Wang, Qiang Fu, et al. "Techniques and Challenges of Image Segmentation: A Review." Electronics 12, no. 5 (2023): 1199. http://dx.doi.org/10.3390/electronics12051199.

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Анотація:

Image segmentation, which has become a research hotspot in the field of image processing and computer vision, refers to the process of dividing an image into meaningful and non-overlapping regions, and it is an essential step in natural scene understanding. Despite decades of effort and many achievements, there are still challenges in feature extraction and model design. In this paper, we review the advancement in image segmentation methods systematically. According to the segmentation principles and image data characteristics, three important stages of image segmentation are mainly reviewed,

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16

Кириллова, Л. К. "Market segmentation: evolution and directions of development in the context of marketing digitalization." Экономика и предпринимательство, no. 1(138) (April 15, 2022): 868–71. http://dx.doi.org/10.34925/eip.2022.138.1.172.

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Анотація:

Статья посвящена вопросам развития сегментирования рынка. Рассмотрена эволюция подходов к сегментации рынка. Обобщен процесс выделения значимых критериев объединения потребителей в группы. Раскрыты принципы сегментации рынка в условиях цифровой экономики. Представлен алгоритм процедуры сегментации потребителей в цифровой среде. The article is devoted to the development of market segmentation. The evolution of approaches to market segmentation is considered. The process of identifying significant criteria for grouping consumers is summarized. The principles of market segmentation in the digital

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17

Yuan, Zhongkai. "Principles, applications, and advancements of the Segment Anything Model." Applied and Computational Engineering 53, no. 1 (2024): 73–78. http://dx.doi.org/10.54254/2755-2721/53/20241270.

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Анотація:

The Segment Anything Model (SAM) is a prominent computer vision model discussed in a review paper focusing on image segmentation. This paper explores the concepts, applications, and advancements of SAM, which excels at accurately separating diverse object types and managing visual data. It leverages convolutional neural networks (CNNs), an encoder-decoder architecture, skip connections, and spatial attention mechanism to capture fine details and contextual information across different scales. SAM finds versatile applications in various domains, including medical imaging for precise anatomical

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18

Bucko, Jozef, Emil Exenberger, and Jana Héjjová. "Balancing the segmentation and behavioral principles towards acquiring customer insight." Transnational Marketing Journal 10, no. 2 (2022): 235–50. http://dx.doi.org/10.33182/tmj.v10i2.1951.

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Digitalization and decentralization within the energy market provide consumers with new opportunities. The trend consequently requires the transformation of energy suppliers’ portfolios beyond energy supply and towards overall household management within business to the customer market. This segment is especially challenging due to its size and variability in habits or behavior related to household management, which includes not only energy supplies but also insurance issues, appliances operations, and service. This study examines, customers’ behavior and their responses to offers of products

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19

Zhang, Wenyin, Yong Wu, Bo Yang, Shunbo Hu, Liang Wu, and Sahraoui Dhelimd. "Overview of Multi-Modal Brain Tumor MR Image Segmentation." Healthcare 9, no. 8 (2021): 1051. http://dx.doi.org/10.3390/healthcare9081051.

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The precise segmentation of brain tumor images is a vital step towards accurate diagnosis and effective treatment of brain tumors. Magnetic Resonance Imaging (MRI) can generate brain images without tissue damage or skull artifacts, providing important discriminant information for clinicians in the study of brain tumors and other brain diseases. In this paper, we survey the field of brain tumor MRI images segmentation. Firstly, we present the commonly used databases. Then, we summarize multi-modal brain tumor MRI image segmentation methods, which are divided into three categories: conventional

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20

Vohra, Sumit K., and Dimiter Prodanov. "The Active Segmentation Platform for Microscopic Image Classification and Segmentation." Brain Sciences 11, no. 12 (2021): 1645. http://dx.doi.org/10.3390/brainsci11121645.

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Image segmentation still represents an active area of research since no universal solution can be identified. Traditional image segmentation algorithms are problem-specific and limited in scope. On the other hand, machine learning offers an alternative paradigm where predefined features are combined into different classifiers, providing pixel-level classification and segmentation. However, machine learning only can not address the question as to which features are appropriate for a certain classification problem. The article presents an automated image segmentation and classification platform,

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21

Zhao, Hui Huang, De Jian Zhou, and Yu Ming Xu. "Research of the SMT Product Character Segmentation Based on Contour Feature." Advanced Materials Research 201-203 (February 2011): 2019–22. http://dx.doi.org/10.4028/www.scientific.net/amr.201-203.2019.

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The principles of the Surface Mount Technology (SMT) product character segmentation and its technology could be described as following: SMT product character image is obtained by image sampling equipment and its ideal binary images is got after image processing. In order to segment the SMT product character effectively, a novel character segmentation algorithm is proposed based on contour feature. Three kinds of information are extracted, one is the up contour feature, another is the under contour feature, the third is the width and the height of the image. Then the position of character segme

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22

Antić, Miloš, Andrej Zdešar, and Igor Škrjanc. "Depth-Image Segmentation based on Evolving Principles for 3D Sensing of Structured Indoor Environments." Sensors 21, no. 13 (2021): 4395. http://dx.doi.org/10.3390/s21134395.

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This paper presents an approach of depth image segmentation based on the Evolving Principal Component Clustering (EPCC) method, which exploits data locality in an ordered data stream. The parameters of linear prototypes, which are used to describe different clusters, are estimated in a recursive manner. The main contribution of this work is the extension and application of the EPCC to 3D space for recursive and real-time detection of flat connected surfaces based on linear segments, which are all detected in an evolving way. To obtain optimal results when processing homogeneous surfaces, we in

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23

Mansurov, Shahzod, Farrukh Mamatov, and Fazliddin Mukhtorov. "COMPARISON OF THE CONCEPTS OF THE BUSINESS SEGMENT AND THE CENTER OF RESPONSIBILITY USED IN THE MANAGEMENT SYSTEM OF RETAIL ENTERPRISES." Science technology & Digital finance 1, no. 4 (2023): 203–8. https://doi.org/10.5281/zenodo.10158147.

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24

Boiko, Bogdan, and Iryna Protcyk. "Classification Model for Effective Employee Segmentation." Modeling, Control and Information Technologies, no. 7 (December 7, 2024): 60–61. https://doi.org/10.31713/mcit.2024.013.

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In this work, an efficient classification model for staff segmentation is developed. The ensemble is based on machine learning principles, allowing the exploration of the performance of various classification methods and the tuning of hyperparameters to optimize system performance. Additionally, it provides the ability to compare the metric results of trained models, enabling the selection of the best strategy for each problem. The work considers an efficient and automated data processing pipeline, which includes data collection, cleaning, and transformation processes that can be applied in va

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25

Aurifeille, Jacques-Marie. "A bio-mimetic approach to marketing segmentation: Principles and comparative analysis." European Journal of Economic and Social Systems 14, no. 1 (2000): 93–108. http://dx.doi.org/10.1051/ejess:2000111.

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26

Garduño, Edgar, Mona Wong-Barnum, Niels Volkmann, and Mark H. Ellisman. "Segmentation of electron tomographic data sets using fuzzy set theory principles." Journal of Structural Biology 162, no. 3 (2008): 368–79. http://dx.doi.org/10.1016/j.jsb.2008.01.017.

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27

Bohnemeyer, Jürgen, Nicholas J. Enfield, James Essegbey, et al. "Principles of event segmentation in language: The case of motion events." Language 83, no. 3 (2007): 495–532. http://dx.doi.org/10.1353/lan.2007.0116.

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28

TKATCHUK, S.V., S.A. STAKHURSKA, and V.O. STAKHURSKIY. "Consumer segmentation in the aspect of food marketing." Market Relations Development in Ukraine №9(244)2021 122 (November 16, 2021): 79–86. https://doi.org/10.5281/zenodo.5704771.

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Consumer segmentation in the aspect of food marketing Relevance of research. The food industry is one of the most strategic areas of activity; it is related to the food security of the country, living standards and health of citizens. Marketing principles of doing business in the food sector should combine several important aspects: purely marketing (market research, customer satisfaction), socially responsible and ethical (high quality products, reliability of information, ethics of advertising, taking into account religious, ethnographic and other features) and physiological (taking into acc

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29

Huang, Xianhua. "Intelligent Algorithms-Based CT Image Segmentation in Patients with Cardiovascular Diseases and Realization of Visualization Algorithms." Scientific Programming 2021 (September 8, 2021): 1–9. http://dx.doi.org/10.1155/2021/2285884.

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The study focused on the intelligent algorithms-based segmentation of computed tomography (CT) images of patients with cardiovascular diseases (CVD) and the realization of visualization algorithms. The first step was to design a method for precise segmentation under the cylinder model based on the coronary body data of the coarse segmentation, and then the principles of different visualization algorithms were discussed. The results showed that the precise segmentation method can effectively eliminate most of the branches and calcified lesions; curved planar reformation (CPR) and straightened C

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30

Cai, Tian Fang, and Zhong Guo Yang. "On the Image Processing Mechanism Based on the Fuzzy Vision." Applied Mechanics and Materials 513-517 (February 2014): 3134–38. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.3134.

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Human visual system has excellent ability in image processing. Based on the visual principles and fuzzy theory, the model of W3M proposed in the paper simulates the level, two-way connectivity, feature detector and learning mechanism of the visual mechanism to a certain extent. The model accomplishes different types of image segmentation by setting different parameters and shows its application potential through the practical application of some really collected biomedical images in segmentation.

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31

Grace, Amelia, Igor Kovalev, Dmitry Kovalev, Kirill Lukyanov, and Dmitry Borovinsky. "Modern approaches to image segmentation in agriculture." E3S Web of Conferences 613 (2025): 03003. https://doi.org/10.1051/e3sconf/202561303003.

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Image segmentation is one of the key areas in computer vision, as it allows for the identification and isolation of distinct regions, objects or structures within an image, which is critical for subsequent analysis and processing of visual data. This article discusses the fundamental principles, capabilities and limitations of various segmentation methods. Special emphasis is placed on the use of the Python programming language, which, thanks to its rich ecosystem of libraries such as OpenCV, TensorFlow, PyTorch, and scikit-image, has become the standard tool for the development and implementa

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32

Todinov, Michael. "Reducing Risk through Segmentation, Permutations, Time and Space Exposure, Inverse States, and Separation." International Journal of Risk and Contingency Management 4, no. 3 (2015): 1–21. http://dx.doi.org/10.4018/ijrcm.2015070101.

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Анотація:

The paper features a number of new generic principles for reducing technical risk with a very wide application area. Permutations of interchangeable components/operations in a system can reduce significantly the risk of system failure at no extra cost. Reducing the time of exposure and the space of exposure can also reduce risk significantly. Technical risk can be reduced effectively by introducing inverse states countering negative effects during service. The application of this principle in logistic supply networks leads to a significant reduction of the risk of congestion and delays. The as

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33

Ma, Xudong, and Yunhe Yu. "Training Tricks for Steel Microstructure Segmentation with Deep Learning." Processes 11, no. 12 (2023): 3298. http://dx.doi.org/10.3390/pr11123298.

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Data augmentation and other training techniques have improved the performance of deep learning segmentation methods for steel materials. However, these methods often depend on the dataset and do not provide general principles for segmenting different microstructural morphologies. In this work, we collected 64 granular carbide images (2048 × 1536 pixels) and 26 blocky ferrite images (2560 × 1756 pixels). We used five carbide images and two ferrite images and derived from them the test set to investigate the influence of frequently used training techniques on model segmentation accuracy. We prop

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34

Engström, Jon, Olof Norin, Serge de Gosson de Varennes, and Aku Valtakoski. "Service design in healthcare: a segmentation-based approach." Journal of Service Management 33, no. 6 (2022): 50–78. http://dx.doi.org/10.1108/josm-06-2021-0239.

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Анотація:

PurposeThe study aims to explore how segmentation as a methodology can be adapted to the healthcare context to provide a more nuanced understanding of the served population and to facilitate the design of patient-centric services.Design/methodology/approachThe study was based on a collaborative project with a national healthcare organization following the principles of action design research. The study describes the quantitative segmentation performed during the project, followed by a qualitative interview study of how segments correspond with patient behaviors in an actual healthcare setting,

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35

Kaldarova, Mira, Akerke Akanova, Akgul Naizagarayeva, Albina Kazanbayeva, and Nazira Ospanova. "Modelling a neural network for analysing the results of segmentation of satellite images." Indonesian Journal of Electrical Engineering and Computer Science 36, no. 1 (2024): 614. http://dx.doi.org/10.11591/ijeecs.v36.i1.pp614-621.

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The study's relevance lies in addressing inaccuracies within satellite image segmentation, necessitating the development and implementation of neural network models for automated segmentation. The purpose of study is to develop a model of a neural network for training with data obtained from the segmentation of satellite images. The basis of the methodological approach in study is a combination of methods of system analysis of neural networks, which have had a substantial impact on the development of the computer vision industry, with an empirical study of the general principles of neural netw

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36

Mira, Kaldarova Akerke Akanova Akgul Naizagarayeva Albina Kazanbayeva Nazira Ospanova. "Modelling a neural network for analysing the results of segmentation of satellite images." Indonesian Journal of Electrical Engineering and Computer Science 36, no. 1 (2024): 614–21. https://doi.org/10.11591/ijeecs.v36.i1.pp614-621.

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Анотація:

The study's relevance lies in addressing inaccuracies within satellite image segmentation, necessitating the development and implementation of neural network models for automated segmentation. The purpose of study is to develop a model of a neural network for training with data obtained from the segmentation of satellite images. The basis of the methodological approach in study is a combination of methods of system analysis of neural networks, which have had a substantial impact on the development of the computer vision industry, with an empirical study of the general principles of neural netw

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37

Perepelytsia, Oleksii, and Oleg Avrunin. "COMPARISON OF THE METHOD OF ELECTROMETRIC DETERMINATION OF ROOT CANAL PARAMETERS AND THE METHOD OF THRESHOLD SEGMENTATION OF RADIOGRAPHS." Innovative Technologies and Scientific Solutions for Industries, no. 4 (22) (December 31, 2022): 48–57. http://dx.doi.org/10.30837/itssi.2022.21.049.

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The subject matter of the article is X-ray images of teeth during endodontic operations. The goal of the work is to compare the developed method of segmentation of the radiograph to determine the length of the root canal with the electrometric and mathematical methods in practice. The article uses the following methods: principles of endodontic preparation of teeth; methods of determining the working length of the root canal (radiological, electrometric); threshold segmentation method; method of segmentation of bone structures on tomographic images. The following results were obtained: the exi

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Moneglia, Massimo, and Emanuela Cresti. "Prosodic segmentation and functional correlations." Journal of Speech Sciences 7, no. 2 (2019): 31–50. http://dx.doi.org/10.20396/joss.v7i2.15001.

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This paper presents a pilot based on the NUCC corpus aimed at verifying the consistency of the Language into Act Theory (L-AcT) for the annotation of information structure in spoken Japanese. L-AcT focus on the perceptual relevance of prosodic breaks, foresees a strict correspondence between prosodic units and information units and bases the Information structure on the unit bearing the illocutionary cues (Comment). The model also foresees a language independent typology of information functions. The pilot shows that the detection of terminal breaks in speech goes hand in hand with the identif

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39

Researcher. "ADVANCED NETWORK SECURITY CONCEPTS: NETWORK SEGMENTATION AND ZERO TRUST ARCHITECTURE." International Journal of Engineering and Technology Research (IJETR) 9, no. 2 (2024): 379–86. https://doi.org/10.5281/zenodo.13851178.

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This article explores two critical concepts in enterprise networking and security: Network Segmentation and Zero Trust Architecture (ZTA). It examines their principles, implementation methods, and benefits in the context of evolving cyber threats and complex IT environments. The article delves into the technical aspects of Network Segmentation, including VLANs, next-generation firewalls, and software-defined networking, as well as the core components of ZTA such as identity and access management, micro-segmentation, and continuous monitoring. The article also analyzes the synergies between the

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40

Ljubojević, Miloš, Mihajlo Savić, Danijel Mijić, and Grujica Vico. "Improving the Efficiency of Multimedia Learning and the Quality of Experience by Reducing Cognitive Load." Applied Sciences 15, no. 3 (2025): 1054. https://doi.org/10.3390/app15031054.

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The design of multimedia teaching materials and the principles of their presentation to students strongly influence distance learning efficiency. The appropriate design of online educational multimedia content became especially important during the period of the COVID-19 crisis. This study presents a methodology for improving the efficiency of multimedia-based distance learning by reducing the cognitive load. Combining the segmentation principle with pauses and testing questions in the design of multimedia teaching materials has a positive influence on reducing the cognitive load in distance l

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41

Peng, Xingshuo, Keyuan Wang, Zelin Zhang, Nan Geng, and Zhiyi Zhang. "A Point-Cloud Segmentation Network Based on SqueezeNet and Time Series for Plants." Journal of Imaging 9, no. 12 (2023): 258. http://dx.doi.org/10.3390/jimaging9120258.

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The phenotyping of plant growth enriches our understanding of intricate genetic characteristics, paving the way for advancements in modern breeding and precision agriculture. Within the domain of phenotyping, segmenting 3D point clouds of plant organs is the basis of extracting plant phenotypic parameters. In this study, we introduce a novel method for point-cloud downsampling that adeptly mitigates the challenges posed by sample imbalances. In subsequent developments, we architect a deep learning framework founded on the principles of SqueezeNet for the segmentation of plant point clouds. In

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42

Spencer, Andrew. "Identifying Stems." Word Structure 5, no. 1 (2012): 88–108. http://dx.doi.org/10.3366/word.2012.0021.

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Programmatic proposals are presented for identifying the boundary between stem and affix in morphologically complex words. This is part of the wider, largely unresearched, problem of segmenting words into morphs. Two principles are proposed for expediting stem segmentation: the Strictly Morphomic Stem Hypothesis (‘all stems are morphomic’) and the Stem Maximization Principle (‘a putative inflection must unambiguously realize a coherent set of morphosyntactic properties, otherwise it is part of a morphomic stem’). It is proposed that there should be a separate stem formation component with esse

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Petrenko, V. "About functional morphology of organism: segmentation and compartmentalization of biosystem." Bulletin of Science and Practice, no. 4 (April 15, 2017): 84–91. https://doi.org/10.5281/zenodo.546283.

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Segmentation and compartmentalization are two sides of the development of organisms in evolution and ontogenesis with the complication of their structure and increase of effectiveness of their function. Evolution uses such way of individual development differently — from simple segmentation of animal body (metamerism of Annelida) to quasi–segmentation in the human body and similar animals (periarterial complexes of organs). It is possible combinative employment both methods of individual organisation. Thus, there are both principles in the construction of lymphatic system — classic metamerism

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Zhang, Ye, Qiu Xie, and Canlin Zhang. "Key Algorithms for Segmentation of Copperplate Printing Image Based on Deep Learning." Mobile Information Systems 2021 (May 25, 2021): 1–10. http://dx.doi.org/10.1155/2021/9940801.

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As a branch of the field of machine learning, deep learning technology is abrupt in various computer vision tasks with its powerful functional learning functions. The deep learning method can extract the required features from the original data and dynamically adjust and update the parameters of the neural network through the backpropagation algorithm so as to achieve the purpose of automatically learning features. Compared with the method of extracting features manually, the recognition accuracy is improved, and it can be used for the segmentation of copperplate printing images. This article

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Eremeev, S. V., and S. A. Romanov. "An Algorithm of Image Segmentation Based on Persistent Homology for Solving Defects Searching Problems." Proceedings of the Southwest State University 24, no. 1 (2020): 144–58. http://dx.doi.org/10.21869/2223-1560-2020-24-1-144-158.

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Purpose of research is to develop an image segmentation algorithm based on the persistent homology for solving problems of searching and classifying defects. The algorithm is aimed at improving the quality of products at enterprises with continuous production (metallurgy, woodworking, and others).Methods. To segment an image, it is proposed to specify links between pixels in the image. In the future, during the iterative breaking of links, as their weights increase, pixels will be combined into groups called holes. Pixels that are in a single group have both their original characteristics and

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A. Ibrahim, Zainab, Nathera A. Saleh, and Murtadha A. Jabbar. "Microstructural Images Segmentation Techniques: A Review." Basrah journal for engineering science 24, no. 1 (2024): 48–56. http://dx.doi.org/10.33971/bjes.24.1.6.

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Image segmentation is the process of automatically dividing an image into distinct, meaningful, and non-overlapping regions. The quality of the segmentation process determines the efficiency of other image processing tasks. Analyzing microstructural images is crucial since the mechanical properties are strongly dependent on the microstructural phases’ statistics. These images are considered one of the most difficult and challenging images to deal with due to their special characteristics, such as the convergence in pixels intensity values, overlapping in colors, boundaries and textures in phas

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Yong, Jiaying. "Comparison of Brain Tumor Segmentation Methods Based on Different Algorithms Using MRI Images." Applied and Computational Engineering 8, no. 1 (2023): 13–17. http://dx.doi.org/10.54254/2755-2721/8/20230057.

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Brain tumor is a serious disease for human beings. MRI is the most widely used method for its innocuousness since people do not need to be exposure to radioactivity. The segmentation on MRI images is a vital step in tumor detection. To improve efficiency and accuracy of the segmentation, scientists apply different algorithms in this process. This paper focuses on three particular algorithms including Connected component label algorithm (CCLA), Watershed algorithm (WSA) and Fuzzy C-means clustering algorithm (FCCA). The principles and applied procedures of these three algorithms are introduced.

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Pinna, Baingio, and Katia Deiana. "New conditions on the role of color in perceptual organization and an extension to how color influences reading." Psihologija 47, no. 3 (2014): 319–51. http://dx.doi.org/10.2298/psi1403319p.

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Color is one among many attributes that are involved in the similarity principle. Grouping by color is believed to be less effective when compared with other attributes such as shape and luminance. The main purpose of this work is to explore the role played by color in determining visual grouping and wholeness, not only in relation to further similarity attributes but also to other principles such as proximity, good continuation and past experience. Conditions, different from those used by Gestalt psychologists, were chosen, and aimed to understand how color can influence visual organization a

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Oko, A. E. Ndu, and Essien E.E. "The Prospects and Challenges of Market Segmentation Practice in the Equipment Leasing Industry of Nigeria 2000-2013." Journal of Business Theory and Practice 2, no. 1 (2014): 28. http://dx.doi.org/10.22158/jbtp.v2n1p28.

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<em>Efficiency in the blending of the marketing mix elements all things being equal is higher among firms whose operations are based on market segmentation principles. Given this, the study appraised the level of adoption of the principle of market segmentation in the equipment leasing industry of Nigeria as it assessed this industry in relation to the nation’s macro economic development. Data base of the research are questionnaire and oral interviews. Findings are that the volume and value of transactions in the equipment lease industry is small thus lessors are involved in scramble mer

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Gupta, Vinayak, Rahul Goel, Sirikonda Dhawal, and P. J. Narayanan. "GSN: Generalisable Segmentation in Neural Radiance Field." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 3 (2024): 2013–21. http://dx.doi.org/10.1609/aaai.v38i3.27972.

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Traditional Radiance Field (RF) representations capture details of a specific scene and must be trained afresh on each scene. Semantic feature fields have been added to RFs to facilitate several segmentation tasks. Generalised RF representations learn the principles of view interpolation. A generalised RF can render new views of an unknown and untrained scene, given a few views. We present a way to distil feature fields into the generalised GNT representation. Our GSN representation generates new views of unseen scenes on the fly along with consistent, per-pixel semantic features. This enables

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