How to Complete Any Segmentation Process Interactively via Image Foresting Transform

2010 ◽  
Author(s):  
P A V Miranda ◽  
Alexandre X Falca ◽  
G C S Ruppert
Keyword(s):  
Segmentation Process ◽  
Image Foresting Transform

ExpanDrogram: Dynamic Visualization of Big Data Segmentation over Time

2021 ◽  
Vol 13 (2) ◽  
pp. 1-27
Author(s):  
A. Khalemsky ◽  
R. Gelbard
Keyword(s):  
Big Data ◽  
Visual Presentation ◽  
Trend Detection ◽  
Dynamic Visualization ◽  
Segmentation Process ◽  
Key Points ◽  
Wide Range ◽  
History Of ◽  
The Individual ◽  
Over Time

In dynamic and big data environments the visualization of a segmentation process over time often does not enable the user to simultaneously track entire pieces. The key points are sometimes incomparable, and the user is limited to a static visual presentation of a certain point. The proposed visualization concept, called ExpanDrogram, is designed to support dynamic classifiers that run in a big data environment subject to changes in data characteristics. It offers a wide range of features that seek to maximize the customization of a segmentation problem. The main goal of the ExpanDrogram visualization is to improve comprehensiveness by combining both the individual and segment levels, illustrating the dynamics of the segmentation process over time, providing “version control” that enables the user to observe the history of changes, and more. The method is illustrated using different datasets, with which we demonstrate multiple segmentation parameters, as well as multiple display layers, to highlight points such as new trend detection, outlier detection, tracking changes in original segments, and zoom in/out for more/less detail. The datasets vary in size from a small one to one of more than 12 million records.

Segmentation of Certificate With Connected Component Labeling Method

2020 ◽  
Vol 8 (2) ◽  
pp. 119
Author(s):  
Cokorda Gde Teresna Jaya ◽  
I Gede Arta Wibawa
Keyword(s):  
Test Data ◽  
Optimization Problem ◽  
Initial Step ◽  
Connected Component ◽  
Important Data ◽  
Connected Component Labeling ◽  
Time Optimization ◽  
Segmentation Process ◽  
Verification Process ◽  
Labeling Method

Certificate is one of the documents that can be used as evidence of ownership or an event. For example, when certificate used as requirement to participate in an event. If a document is made as a requirement, of course the file verification process will be done. Seeing the time optimization problem when verifying the file, the authors carry out research by segmenting important data contained in a certificate as an initial step in the development of an automatic document verification system. The segmentation process carried out in this study uses the Connected Component Labeling method in determining the area to be segmented and Automatic Cropping to cut the results of the segmentation process. By using these two methods obtained an accuracy of 60% with a total of 15 pieces of test data

The eve stripe 2 enhancer employs multiple modes of transcriptional synergy

Development ◽  
1996 ◽  
Vol 122 (1) ◽  
pp. 205-214 ◽  
Author(s):  
D.N. Arnosti ◽  
S. Barolo ◽  
M. Levine ◽  
S. Small
Keyword(s):  
Fusion Protein ◽  
Drosophila Embryo ◽  
Cooperative Binding ◽  
Synergistic Activity ◽  
Detailed Model ◽  
Multiple Modes ◽  
Anterior Half ◽  
Segmentation Process ◽  
Transgenic Embryos ◽  
Cis And Trans

Previous studies have provided a detailed model for the regulation of even-skipped (eve) stripe 2 expression in the Drosophila embryo. The bicoid (bcd) regulatory gradient triggers the expression of hunchback (hb); these work synergistically to activate the stripe in the anterior half of the embryo, bcd also coordinates the expression of two repressors, giant (gt) and Kruppel (Kr), which define the anterior and posterior borders of the stripe, respectively. Here, we report the findings of extensive cis- and trans- complementation analyses using a series of defective stripe 2 enhancers in transgenic embryos. This study reaches two primary conclusions. First, the strip 2 enhancer is inherently ‘sensitized’ for repression by gt. We propose that gt specifies the sharp anterior stripe border by blocking two tiers of transcriptional synergy, cooperative binding to DNA and cooperative contact of bound activators with the transcription complex. Second, we find that the synergistic activity of hb and bcd is ‘promiscuous’. For example, a maternally expressed Gal4-Sp1 fusion protein can functionally replace hb in the stripe 2 enhancer. This finding challenges previous proposals for dedicated hb and bcd interactions in the segmentation process.

Development and evaluation of an automatic text annotation system for supporting digital humanities research

2019 ◽  
Vol 37 (3) ◽  
pp. 436-455 ◽  
Author(s):  
Chih-Ming Chen ◽  
Yung-Ting Chen ◽  
Chen-Yu Liu
Keyword(s):  
Technology Acceptance ◽  
Digital Humanities ◽  
Word Segmentation ◽  
Ancient Text ◽  
Content Type ◽  
Text Annotation ◽  
Annotation System ◽  
Segmentation Process ◽  
Automatic Text ◽  
Ancient Texts

Purpose An automatic text annotation system (ATAS) that can collect resources from different databases through Linked Data (LD) for automatically annotating ancient texts was developed in this study to support digital humanities research. It allows the humanists referring to resources from diverse databases when interpreting ancient texts as well as provides a friendly text annotation reader for humanists interpreting ancient text through reading. The paper aims to discuss whether the ATAS is helpful to support digital humanities research or not. Design/methodology/approach Based on the quasi-experimental design, the ATAS developed in this study and MARKUS semi-ATAS were compared whether the significant differences in the reading effectiveness and technology acceptance for supporting humanists interpreting ancient text of the Ming dynasty’s collections existed or not. Additionally, lag sequential analysis was also used to analyze users’ operation behaviors on the ATAS. A semi-structured in-depth interview was also applied to understand users’ opinions and perception of using the ATAS to interpret ancient texts through reading. Findings The experimental results reveal that the ATAS has higher reading effectiveness than MARKUS semi-ATAS, but not reaching the statistically significant difference. The technology acceptance of the ATAS is significantly higher than that of MARKUS semi-ATAS. Particularly, the function comparison of the two systems shows that the ATAS presents more perceived ease of use on the functions of term search, connection to source websites and adding annotation than MARKUS semi-ATAS. Furthermore, the reading interface of ATAS is simple and understandable and is more suitable for reading than MARKUS semi-ATAS. Among all the considered LD sources, Moedict, which is an online Chinese dictionary, was confirmed as the most helpful one. Research limitations/implications This study adopted Jieba Chinese parser to perform the word segmentation process based on a parser lexicon for the Chinese ancient texts of the Ming dynasty’s collections. The accuracy of word segmentation to a lexicon-based Chinese parser is limited due to ignoring the grammar and semantics of ancient texts. Moreover, the original parser lexicon used in Jieba Chinese parser only contains the modern words. This will reduce the accuracy of word segmentation for Chinese ancient texts. The two limitations that affect Jieba Chinese parser to correctly perform the word segmentation process for Chinese ancient texts will significantly affect the effectiveness of using ATAS to support digital humanities research. This study thus proposed a practicable scheme by adding new terms into the parser lexicon based on humanists’ self-judgment to improve the accuracy of word segmentation of Jieba Chinese parser. Practical implications Although some digital humanities platforms have been successfully developed to support digital humanities research for humanists, most of them have still not provided a friendly digital reading environment to support humanists on interpreting texts. For this reason, this study developed an ATAS that can automatically retrieve LD sources from different databases on the Internet to supply rich annotation information on reading texts to help humanists interpret texts. This study brings digital humanities research to a new ground. Originality/value This study proposed a novel ATAS that can automatically annotate useful information on an ancient text to increase the readability of the ancient text based on LD sources from different databases, thus helping humanists obtain a deeper and broader understanding in the ancient text. Currently, there is no this kind of tool developed for humanists to support digital humanities research.

scholarly journals Capsule Networks as Recurrent Models ofGrouping and Segmentation

2019 ◽  
Author(s):  
Adrien Doerig ◽  
Lynn Schmittwilken ◽  
Bilge Sayim ◽  
Mauro Manassi ◽  
Michael H. Herzog
Keyword(s):  
Neural Networks ◽  
Visual System ◽  
Convolutional Neural Networks ◽  
Human Vision ◽  
Global Shape ◽  
Grouping And Segmentation ◽  
Segmentation Process ◽  
Shape Processing ◽  
Visual Crowding ◽  
Recurrent Connections

AbstractClassically, visual processing is described as a cascade of local feedforward computations. Feedforward Convolutional Neural Networks (ffCNNs) have shown how powerful such models can be. However, using visual crowding as a well-controlled challenge, we previously showed that no classic model of vision, including ffCNNs, can explain human global shape processing (1). Here, we show that Capsule Neural Networks (CapsNets; 2), combining ffCNNs with recurrent grouping and segmentation, solve this challenge. We also show that ffCNNs and standard recurrent CNNs do not, suggesting that the grouping and segmentation capabilities of CapsNets are crucial. Furthermore, we provide psychophysical evidence that grouping and segmentation are implemented recurrently in humans, and show that CapsNets reproduce these results well. We discuss why recurrence seems needed to implement grouping and segmentation efficiently. Together, we provide mutually reinforcing psychophysical and computational evidence that a recurrent grouping and segmentation process is essential to understand the visual system and create better models that harness global shape computations.Author SummaryFeedforward Convolutional Neural Networks (ffCNNs) have revolutionized computer vision and are deeply transforming neuroscience. However, ffCNNs only roughly mimic human vision. There is a rapidly expanding body of literature investigating differences between humans and ffCNNs. Several findings suggest that, unlike humans, ffCNNs rely mostly on local visual features. Furthermore, ffCNNs lack recurrent connections, which abound in the brain. Here, we use visual crowding, a well-known psychophysical phenomenon, to investigate recurrent computations in global shape processing. Previously, we showed that no model based on the classic feedforward framework of vision can explain global effects in crowding. Here, we show that Capsule Neural Networks (CapsNets), combining ffCNNs with recurrent grouping and segmentation, solve this challenge. ffCNNs and recurrent CNNs with lateral and top-down recurrent connections do not, suggesting that grouping and segmentation are crucial for human-like global computations. Based on these results, we hypothesize that one computational function of recurrence is to efficiently implement grouping and segmentation. We provide psychophysical evidence that, indeed, grouping and segmentation is based on time consuming recurrent processes in the human brain. CapsNets reproduce these results too. Together, we provide mutually reinforcing computational and psychophysical evidence that a recurrent grouping and segmentation process is essential to understand the visual system and create better models that harness global shape computations.

scholarly journals THE PROCEDURE OF DEVELOPMENT OF INTERNATIONAL MARKET SEGMENTATION STRATEGY

2020 ◽  
pp. 166-182
Author(s):  
Olga Prygara ◽  
Viktoria Zhurylo
Keyword(s):  
Market Segmentation ◽  
International Market ◽  
International Markets ◽  
Individual Characteristics ◽  
Entrepreneurial Activity ◽  
Cultural Environment ◽  
Market Demand ◽  
Market Environment ◽  
Segmentation Strategy ◽  
Segmentation Process

Introduction. Increase of intensity of international economic activity under the process of internationalization of commodity markets lead to the necessity of search of attractive international markets and segments. Aim of the article is the development of procedure of international market segmentation strategy and determination of peculiarities of international market segmentation in comparison with segmentation of domestic markets, considering the necessity of evaluation of factors of choice of attractive markets, considering the influence of cultural environment on entrepreneurial activity. Method (Methodology). Application of methods of scientific generalization, analysis and synthesis gave an opportunity to distinguish elements, that characterize segmentation of international markets; to systemize the factors of international market environment, that influence international market segmentation process, define customers’ characteristics, that influence their purchasing decisions; to distinguish stages of international market segmentation; to describe features and marketing tasks of each stage. Results. Segmentation of international markets has to be viewed as the systematized process of division of international markets on the groups of countries and groups of individual customers on the basis of their cultural values and motivations concerning their decision making process, that gives an opportunity to satisfy their specific needs and strengthen international competitive positions. The factors that influence international segmentation process are macrofactors: geographic, structural-demographic, legal, economic, scientific, socio-cultural; and microfactors: common market factors (market demand, competitive factors, factors of quality characteristics of the product) and customer-based factors (psychological, behavioral, individual characteristics of customers). The stages of the procedure of developing of international segmentation strategy are: market attractiveness evaluation; competitive analysis; demand evaluation; cultural environment analysis; macrosegmentation of markets; microsegmentation of markets; implementation of strategy and control. The proposed strategy of international segmentation strategy requires forming of the detailed marketing plan to a certain market segment and constant monitoring of its realization in accordance with changes in market environment and motivations of customers.

scholarly journals SELECTED APPLICATIONS OF DEEP NEURAL NETWORKS IN SKIN LESION DIAGNOSTIC

2021 ◽  
Vol 11 (4) ◽  
pp. 18-21
Author(s):  
Magdalena Michalska
Keyword(s):  
Neural Networks ◽  
Malignant Melanoma ◽  
Skin Lesion ◽  
Deep Neural Networks ◽  
Skin Lesions ◽  
Multiclass Classification ◽  
Features Selection ◽  
Lesion Segmentation ◽  
Dermatological Diseases ◽  
Segmentation Process

The article provides an overview of selected applications of deep neural networks in the diagnosis of skin lesions from human dermatoscopic images, including many dermatological diseases, including very dangerous malignant melanoma. The lesion segmentation process, features selection and classification was described. Application examples of binary and multiclass classification are given. The described algorithms have been widely used in the diagnosis of skin lesions. The effectiveness, specificity, and accuracy of classifiers were compared and analysed based on available datasets.

scholarly journals SEGMENTASI CITRA THORAX PARU-PARU MANUSIA DARI SINAR-X MENGGUNAKAN METODE KONTUR AKTIF

2019 ◽  
Vol 4 (2) ◽  
pp. 8-10
Author(s):  
Sintha Syaputri ◽  
Zulkarnain
Keyword(s):  
Active Contour ◽  
Active Contours ◽  
Contour Method ◽  
Image Objects ◽  
Contour Segmentation ◽  
Segmentation Process ◽  
Coordinate Position ◽  
Image Improvement ◽  
The Right

Research on medical image objects in the form of lung images of thoracic X-Rayis increasingly being developed because the information contained in medical images is used to analyze and determine the shape of the lungs. The process of normalization and image improvement is needed and continued with the segmentation process using the right method. The active snake contour method is used because it is resistant to the noise around the object. The research has been usedthe Matlab software GUI program version R2015a. The image through the initial preprocessing stage is converted into a grayscale image. The segmentation process used after the initialization process in the form of a small circle curve placed of the object to be segmented and the determination position of the active contour or detemination of the active parameters of the contour. Determination of the value active contour parameters greatly influences the results of segmentation and influences the direction of active contour movement. If the active coordinate position of the contour is outside the area to be segmented it will cause active contours to move away from the object. Validation the level of accuracy of segmentation results is done by comparing the results of the snake active contour segmentation to the results of manual segmentationused MSE method

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