Search Results - (( fraud detection method algorithm ) OR ( leaf optimization method algorithm ))
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Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff
Published 2014“…The new algorithm is tested on simulated and real data where the results show it is capable of detecting fraud activities. …”
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Fraud detection in telecommunication industry using Gaussian mixed model
Published 2013“…In this article, we propose a new fraud detection algorithm using Gaussian mixed model (GMM), a probabilistic model successfully used in speech recognition problem. …”
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Credit Card Fraud Detection Using AdaBoost and Majority Voting
Published 2018“…In this paper, machine learning algorithms are used to detect credit card fraud. Standard models are first used. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…It provides an increased convergence and globally optimized solutions. The algorithm has been tested using actual customer consumption data from SESB. 10 fold cross validation method is used to confirm the consistency of the detection accuracy. …”
Conference Paper -
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Improved expectation maximization algorithm for Gaussian mixed model using the kernel method
Published 2013“…Finally, for illustration, we apply the improved algorithm to real telecommunication data. The modified method will pave the way to introduce a comprehensive method for detecting fraud calls in future work.…”
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Employing Artificial Intelligence to Minimize Internet Fraud
Published 2009“…Following this, an a ttempt is made to propose using the MonITARS (Monitoring In sider Trading and Regulatory Surveillance) Systems framework which uses a combination of genetic algorithms, neural nets and statistical analysis in detecting insider dealing, to be used in the detection of transaction fraud. …”
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Outlier Detection Technique in Data Mining: A Research Perspective
Published 2005“…The identification of outliers can lead to the discovery of unexpected knowledge in areas such as credit card fraud detection, calling card fraud detection, discovering criminal behaviors, discovering computer intrusion, etc. …”
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A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh
Published 2019“…The empirical results positively indicate that the hybrid model with the sliding window method is able to yield a good accuracy rate of 82.4% in detecting fraud cases in real world credit card transactions. …”
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Automated plant classification system using a hybrid of shape and color features of the leaf
Published 2016“…Automated plant leaf classification is a computerized approach that employs computer vision and machine learning algorithms to identify a plant based on the features of its leaf. …”
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10
Leaf condition analysis using convolutional neural network and vision transformer
Published 2024“…Besides, existing leaf disease detection programs do not provide an optimized user’s experience. …”
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Plant leaf recognition algorithm using ant colony-based feature extraction technique
Published 2013“…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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SEDF: a spoofed email detection framework employed by a lightweight web browser plug-in for detecting the spoofed email / Al Ya@Geogiana Buja...[et al.]
Published 2014“…The method used to detect fake e-mail is by tracing back the email header. …”
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Research Reports -
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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14
Intelligent deep machine learning cyber phishing URL detection based on BERT features extraction
Published 2022“…The results showed that the proposed method was efficient and valid in detecting phishing websites’ URLs.…”
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A comparative analysis of anti-phishing website techniques: identifying optimal approaches to enhance cybersecurity
Published 2023“…Consequently, it is critical to identify effective detection techniques for fraudulent websites. The research consists of analysing the characteristics of phishing websites, extracting their essential features using the wrapper method, and classifying websites as phishing or legitimate using supervised and unsupervised learning algorithms. …”
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Final Year Project / Dissertation / Thesis -
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Deep plant: A deep learning approach for plant classification / Lee Sue Han
Published 2018“…They look for the procedures or algorithms that maximize the use of leaf databases for plant predictive modelling, but this results in leaf features which are liable to change with different leaf data and feature extraction techniques. …”
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17
Enhancing battery state of charge estimation through hybrid integration of barnacles mating optimizer with deep learning
“…In response to the growing importance of SoC estimation, this study introduces a hybrid approach called the Barnacles Mating Optimizer with Deep Learning (BMO-DL) for SoC of Nissan Leaf batteries. …”
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Introducing new statistical shape based and texture feature extraction methods in the plant species recognition system
Published 2013“…The results show the outperformance of the two proposed methods for image processing and optimized classifier for classification part. …”
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