检索结果-南通市图书馆

Nature-Inspired Level Set Segmentation Model for 3D-MRI Brain Tumor Detection

Computers, Materials & Continua 2021年第7期68卷 961-981页

作者： oday ali hassen Sarmad Omar Abter Ansam A.Abdulhussein Saad M.Darwish Yasmine M.Ibrahim Walaa Sheta Department of Computer Techniques Engineering Imam Al-Kadhum College(IKC)WasitIraq University of Information Technology and Communications Media Technology Engineering DepartmentIraq University of Information Technology and Communications Baghdad10081Iraq Department of Information Technology Institute of Graduate Studies and ResearchAlexandria University63 Horreya AvenueEl–ShatbyAlexandria21526Egypt Informatics Research Institute City of Scientific Research and Technology ApplicationsBorg EL Arab21934Egypt

Medical image segmentation has consistently been a significant topic of research and a prominent goal,particularly in computer *** tumor research plays a major role in medical imaging applications by providing a tremendous amount of anatomical and functional knowledge that enhances and allows easy diagnosis and disease therapy *** prevent or minimize manual segmentation error,automated tumor segmentation,and detection became the most demanding process for radiologists and physicians as the tumor often has complex *** methods for detection and segmentation presently exist,but all lack high *** paper’s key contribution focuses on evaluating machine learning techniques that are supposed to reduce the effect of frequently found issues in brain tumor ***,attention concentrated on the challenges related to level set *** study proposed in this paper uses the Population-based Artificial Bee Colony Clustering(P-ABCC)methodology to reliably collect initial contour points,which helps minimize the number of iterations and segmentation errors of the level-set *** proposed model measures cluster centroids(ABC populations)and uses a level-set approach to resolve contour differences as brain tumors vary as they have irregular form,structure,and *** suggested model comprises of three major steps:first,pre-processing to separate the brain from the head and improves contrast ***,P-ABCC is used to obtain tumor edges that are utilized as an initial MRI sequence *** level-set segmentation is then used to detect tumor regions from all volume slices with fewer *** suggest improved model efficiency compared to state-of-the-art methods for both datasets BRATS 2019 and BRATS *** BRATS 2019,dice progress was achieved for Entire Tumor(WT),Tumor Center(TC),and Improved Tumor(ET)by 0.03%,0.03%,and 0.01%*** BRATS 2017,an increase in precision for WT was reac

关键词： 3D-MRI tumor diagnosis bio-inspired clustering ABC optimization multimodal detection

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Fusion of Type-2 Neutrosophic Similarity Measure in Signatures Verification Systems: A New Forensic Document Analysis Paradigm

引用

Intelligent Automation & Soft Computing 2024年第5期39卷 805-828页

作者： Shahlaa Mashhadani Wisal Hashim Abdulsalam oday ali hassen Saad M.Darwish Department of Computer College of Education for Pure Sciences Ibn Al-HaithamUniversity of BaghdadBaghdad10071Iraq Ministry of Education Wasit Education DirectorateKut52001Iraq Department of Information Technology Institute of Graduate Studies and ResearchAlexandria UniversityEl ShatbyP.O.Box 832Alexandria21526Egypt

Signature verification involves vague situations in which a signature could resemble many reference samples ormight differ because of handwriting variances. By presenting the features and similarity score of signatures from thematching algorithm as fuzzy sets and capturing the degrees of membership, non-membership, and indeterminacy,a neutrosophic engine can significantly contribute to signature verification by addressing the inherent uncertaintiesand ambiguities present in signatures. But type-1 neutrosophic logic gives these membership functions fixed values,which could not adequately capture the various degrees of uncertainty in the characteristics of signatures. Type-1neutrosophic representation is also unable to adjust to various degrees of uncertainty. The proposed work exploresthe type-2 neutrosophic logic to enable additional flexibility and granularity in handling ambiguity, indeterminacy,and uncertainty, hence improving the accuracy of signature verification systems. Because type-2 neutrosophiclogic allows the assessment of many sources of ambiguity and conflicting information, decision-making is moreflexible. These experimental results show the possible benefits of using a type-2 neutrosophic engine for signatureverification by demonstrating its superior handling of uncertainty and variability over type-1, which eventuallyresults in more accurate False Rejection Rate (FRR) and False Acceptance Rate (FAR) verification results. In acomparison analysis using a benchmark dataset of handwritten signatures, the type-2 neutrosophic similaritymeasure yields a better accuracy rate of 98% than the type-1 95%.

关键词： Type-2 neutrosophic reasoning biometric signature verification forensic document experts’ analysis

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Realistic Smile Expression Recognition Approach Using Ensemble Classifier with Enhanced Bagging

引用

Computers, Materials & Continua 2022年第2期70卷 2453-2469页

作者： oday A.hassen Nur Azman Abu Zaheera Zainal Abidin Saad M.Darwish University Technical Malaysia Melaka Department of Information TechnologyMelaka76100Malaysia Institute of Graduate Studies and Research University of AlexandriaAlexandriaEl Shatby21526Egypt

A robust smile recognition system could be widely used for many real-world *** of a facial smile in an unconstrained setting is difficult due to the invertible and wide variety in face *** this paper,an adaptive model for smile expression classification is suggested that integrates a fast features extraction algorithm and cascade *** model takes advantage of the intrinsic association between face detection,smile,and other face features to alleviate the over-fitting issue on the limited training set and increase classification *** features are extracted taking into account to exclude any unnecessary coefficients in the feature vector;thereby enhancing the discriminatory capacity of the extracted features and reducing the computational ***,the main causes of error in learning are due to noise,bias,and *** helps to minimize these *** of multiple classifiers decrease variance,especially in the case of unstable classifiers,and may produce a more reliable classification than a single ***,a shortcoming of bagging as the best ensemble classifier is its random selection,where the classification performance relies on the chance to pick an appropriate subset of training *** suggested model employs a modified form of bagging while creating training sets to deal with this challenge(error-based bootstrapping).The experimental results for smile classification on the JAFFE,CK+,and CK+48 benchmark datasets show the feasibility of our proposed model.

关键词： Ensemble classifier smile expression detection features extraction

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

An Adaptive Privacy Preserving Framework for Distributed Association Rule Mining in Healthcare Databases

引用

Computers, Materials & Continua 2023年第2期74卷 4119-4133页

作者： Hasanien K.Kuba Mustafa A.Azzawi Saad M.Darwish oday A.hassen Ansam A.Abdulhussein University of Information Technology and Communication(UOITC) Baghdad10081Iraq Accenture Ling Karan TRXKuala Lumpur55188Malaysia Department of Information Technology Institute of Graduate Studies and ResearchUniversity of Alexandria21526Egypt Ministry of Education Wasit Education DirectorateKut52001Iraq Information Technology Center Iraqi Commission for Computers and InformaticsBaghdad10081Iraq

It is crucial,while using healthcare data,to assess the advantages of data privacy against the possible *** from several sources must be combined for use in many data mining *** medical practitioner may use the results of association rule mining performed on this aggregated data to better personalize patient care and implement preventive ***,numerous heuristics(e.g.,greedy search)and metaheuristics-based techniques(e.g.,evolutionary algorithm)have been created for the positive association rule in privacy preserving data mining(PPDM).When it comes to connecting seemingly unrelated diseases and drugs,negative association rules may be more informative than their positive *** is well-known that during negative association rules mining,a large number of uninteresting rules are formed,making this a difficult problem to *** this research,we offer an adaptive method for negative association rule mining in vertically partitioned healthcare datasets that respects users’*** applied approach dynamically determines the transactions to be interrupted for information hiding,as opposed to predefining *** study introduces a novel method for addressing the problem of negative association rules in healthcare data mining,one that is based on the Tabu-genetic optimization *** search is advantageous since it removes a huge number of unnecessary rules and item *** using benchmark healthcare datasets prove that the discussed scheme outperforms state-of-the-art solutions in terms of decreasing side effects and data distortions,as measured by the indicator of hiding failure.

关键词： Distributed data mining evolutionary computation sanitization process healthcare informatics

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：