Fleckmentation: rapid segmentation using repeated 2‐means

Rasche, Christoph

doi:10.1049/iet-ipr.2018.6060

Cited by 6 publications

(5 citation statements)

References 21 publications

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“…If the attribute variable is categorical, the chi-square test is used; if the attribute variable is distant, the F test is used. If there are significant differences in the means, the 2-Means clustering method is used to cluster the samples into two categories, including the initial extreme centers of the two extreme means, so that the target variable values are merged into two categories [ 23 , 24 ].…”

Section: Programs Methodsmentioning

confidence: 99%

Implementation of organization and end-user computing-anti-money laundering monitoring and analysis system security control

Sun

2021

PLoS ONE

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The Monitoring and Analysis Centre for the fight against money laundering is a valid financial information body which is responsible for collecting, analysing and providing financial information and conducting international exchanges of financial information for relevant undertakings. By constructing the analysis of the monitoring of the local and foreign currency and of the data transmission subsystem in the plan for the transitional period against In the light of the above, the Commission will continue to monitor the implementation of the acquis in the light of the progress made in implementing the acquis future new systems. The purpose of this paper is to study the research and implementation of the security control of the anti-money laundering monitoring and analysis system. This article studies the application of decision tree analysis technology in the anti-money laundering monitoring system of insurance companies to achieve the purpose of improving the anti-money laundering monitoring technology and capabilities of insurance companies. The emergence of data mining technology provides a new system solution for anti-money laundering monitoring. For insurance anti-money laundering, how to find potential money laundering cases in suspicious and large surrender transactions is key. The experimental data show that the decision tree method is the best predictor of the customer category between the insurance application and the surrender days. The decision tree analysis technology has greatly improved the security monitoring capabilities of the insurance in the anti-money laundering monitoring system. Experimental data shows that the security control capabilities of the anti-money laundering monitoring and analysis system make the accuracy of the entire model reach 95%, the accuracy of large and suspicious transactions reaches 88.6%, and the correct classification of customers is about 99.6%.

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Section: Programs Methodsmentioning

confidence: 99%

Implementation of organization and end-user computing-anti-money laundering monitoring and analysis system security control

Sun

2021

PLoS ONE

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“…Fig. 12 shows an example for one logical map, obtained from a segmentation process using a clustering algorithm [45]. Most symmetric axes can be understood as one of the three cases we have discussed in Fig.…”

Section: Methodsmentioning

confidence: 99%

“… Symmetric axes for a grey‐scale image (first airport image of UCMD collection). The logical map represents the second depth of the fleckmentation process used in [45 ]. The symmetric axes are in colour red [in pdf file] …”

Section: Methodsmentioning

confidence: 99%

“…One collection was the Urban&Natural collection by Oliva and Torralba [53]. For each of those collections, four region types are extracted, taken from three sources: the brighter and darker regions from the difference‐of‐Gaussian scale space; the regions between edge contours; and regions from clustering [45]; this totals 16 lists of region descriptors, see also Fig. 1 in [46], the four sets of feature maps to the right.…”

Section: Applicationsmentioning

confidence: 99%

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Rapid region analysis for classification

Rasche

2020

IET image process

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“…Segmentation algorithms, based on structural analysis, continue to be used, often as an ensemble of segmentation techniques, especially in critical applications, such as lesion localization [10,11]. Other approaches, based on biased normalized cuts or light techniques, are also devised [12,13]. Many studies have also been conducted in the segmentation and classification of cells from digital images.…”

Section: Introductionmentioning

confidence: 99%

A Smartphone-Based Cell Segmentation to Support Nasal Cytology

et al. 2020

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Rhinology studies the anatomy, physiology, and diseases affecting the nasal region—one of the most modern techniques to diagnose these diseases is nasal cytology, which involves microscopic analysis of the cells contained in the nasal mucosa. The standard clinical protocol regulates the compilation of the rhino-cytogram by observing, for each slide, at least 50 fields under an optical microscope to evaluate the cell population and search for cells important for diagnosis. The time and effort required for the specialist to analyze a slide are significant. In this paper, we present a smartphones-based system to support cell segmentation on images acquired directly from the microscope. Then, the specialist can analyze the cells and the other elements extracted directly or, alternatively, he can send them to Rhino-cyt, a server system recently presented in the literature, that also performs the automatic cell classification, giving back the final rhinocytogram. This way he significantly reduces the time for diagnosing. The system crops cells with sensitivity = 0.96, which is satisfactory because it shows that cells are not overlooked as false negatives are few, and therefore largely sufficient to support the specialist effectively. The use of traditional image processing techniques to preprocess the images also makes the process sustainable from the computational point of view for medium–low end architectures and is battery-efficient on a mobile phone.

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Fleckmentation: rapid segmentation using repeated 2‐means

Cited by 6 publications

References 21 publications

Implementation of organization and end-user computing-anti-money laundering monitoring and analysis system security control

Implementation of organization and end-user computing-anti-money laundering monitoring and analysis system security control

Rapid region analysis for classification

A Smartphone-Based Cell Segmentation to Support Nasal Cytology

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