Search Results - (( using case method algorithm ) OR ( software classification methods algorithm ))

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  1. 1

    Blood cell image segmentation using unsupervised clustering techniques by Tuan Muda, Tuan Zalizam, Abdul Salam, Rosalina

    Published 2009
    “…Blood cell images have become particularly useful in medical diagnostic tools for cases involving blood. …”
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    Conference or Workshop Item
  2. 2

    Image authentication using Zernike moment watermarking by Shojanazeri, Hamid

    Published 2013
    “…The adding or replacing a portion of the image is regarded as malicious attacks and rejected by this algorithm. Using two different watermarks lead to a good classification of incidental and malicious modifications and locating the tampered areas. …”
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    Thesis
  3. 3

    Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition by Muhammad Arif, Mohamad, Zalili, Musa, Amelia Ritahani, Ismail

    Published 2023
    “…The algorithm experiments are carried out using the chain code representation created from previous research of the Centre of Excellence for Document Analysis and Recognition (CEDAR) dataset, which consists of 126 upper-case letter characters. …”
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  4. 4

    A Framework For Classification Software Security Using Common Vulnerabilities And Exposures by Hassan, Nor Hafeizah

    Published 2018
    “…This inclusive of the investigation of vulnerability classification objectives,processes,classifiers and focus domains among prominent framework.Final step is to construct the framework by establishing the formal presentation of the vulnerability classification algo-rithm.The validation process was conducted empirically using statistical method to assess the accuracy and consistency by using the precision and recall rate of the algorithm on five data sets each with 500 samples.The findings show a significant result with precision's error rate or p value is between 0.01 and 0.02 with error rate for recall's error rate is between 0.02 and 0.04.Another validation was conducted to verify the correctness of the classification by using expert opinions,and the results showed that the ambiguity of several cases were subdue. …”
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    Thesis
  5. 5

    Development of Scoliotic spine severity detection using deep learning Algorithms by Makhdoomi, Nahid Ameer, Gunawan, Teddy Surya, Idris, Nur Hanani, Khalifa, Othman Omran, Karupiah, Rajandra Kumar, Bramantoro, Arif, Abdul Rahman, Farah Diyana, Zakaria@Mohamad, Zamzuri

    Published 2022
    “…Using Convolutional Neural Network (CNN), this research will integrate an artificial intelligence-assisted method for detecting and classifying Scoliosis illness types. …”
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    Proceeding Paper
  6. 6

    Filter-wrapper based feature ranking technique for dynamic software quality attributes by Kamaruddin, Siti Sakira, Yahaya, Jamaiah, Deraman, Aziz, Ahmad, Ruzita

    Published 2012
    “…This article presents a filter-wrapper based feature ranking technique that is able to learn and rank quality attributes according to new cases of software quality assessment data.The proposed feature ranking technique consists of a scoring method named Most Priority of Feature (MPF) and a learning algorithm to learn the software quality attribute weights. …”
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  7. 7

    Comparative Analysis Using Bayesian Approach To Neural Network Of Translational Initiation Sites In Alternative Polymorphic Contex by Herman, Nanna Suryana, Husin, Nurul Arneida, Hussin, Burairah

    Published 2012
    “…The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study.The first approach of neural network includes training on algorithms of Resilient Backpropagation,Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt.The outputs are used in comparison with Bayesian Neural Network for efficiency comparison.The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy.In second approach,the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%.The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method,and increasing the length of the window sequence to 201.The result shows that the built model successfully increases the accuracy by 96.0%.In comparison,the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%. …”
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    Article
  8. 8

    Software defect prediction framework based on hybrid metaheuristic optimization methods by Wahono, Romi Satria

    Published 2015
    “…The classification algorithm is a popular machine learning approach for software defect prediction. …”
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    Thesis
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    Non-Invasive Diabetes Level Monitoring System using Artificial Intelligence and UWB by Islam, Minarul, Sabira, Khatun, Shoumy, Nusrat Jahan, Ali, Md Shawkat, Mohamad Shaiful, Abdul Karim, Bari, Bifta Sama

    Published 2020
    “…To overcome this drawbacks, a non-invasive ul-tra-wideband (UWB) BGCL measurement system is proposed here with en-hanced software module. The hardware can be controlled through the graphical user interface (GUI) of software and can execute signal processing, feature ex-traction, and feature classification using artificial intelligence (AI). …”
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    Data Mining Approach To Classify Covid-19 Severity By Clinical Symptoms by Kanyan, Laura Jasmine Thomas

    Published 2021
    “…Missing values were treated using filtering and imputation methods. The classification algorithms: J48, SMO, Random Forest, and Simple Logistic were executed and tested to classify data into three classes: mild, moderate, and severe. …”
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    Monograph
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