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  1. 1

    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…A working classification algorithm is developed by using MATLAB and the Fuzzy Logic Toolbox to differentiate and classify the staining pattern of HEp-2 cell images. …”
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    Final Year Project
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    Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

    Published 2021
    “…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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    Final Year Project
  4. 4

    HEp-2 cell images classification based on statistical texture analysis and fuzzy logic by Jamil, N.F.B., Faye, I., May, Z.

    Published 2014
    “…This paper proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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    Conference or Workshop Item
  5. 5

    Classification Of Cervical Cancer Stage From Pap Smear Tests by Sendal, Ken Irok

    Published 2019
    “…The performance of the proposed classification algorithm gave satisfactory results of accuracy, 91.9% for KNN classification and 95.0% for SVM classification.…”
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    Final Year Project
  6. 6

    An Adaptive Fuzzy Contrast Enhancement Algorithm with Details Preserving by Jing, Rui Tang, Mat Isa, Nor Ashidi

    Published 2014
    “…In addition, the experiments using cervical cell images and HEp-2 cell images showed great potential of the AFCEDP technique as a technique for enhancing medical microscopic images.…”
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    Article
  7. 7

    An Intelligent Detection System for Rheumatoid Arthritis (RA) Disease using Image Processing by Hajyyev, Abdyrahym

    Published 2014
    “…The images obtained from MIVIA dataset has been manually segmented to cell level from the image level. Developing an automated segmentation algorithm might give better results.…”
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    Final Year Project
  8. 8

    Classification of Diabetes Mellitus using Ensemble Algorithms by Noor, N.A.B.S., Elamvazuthi, I., Yahya, N.

    Published 2021
    “…The objective of this study is to perform DM classification using various machine learning algorithms. …”
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    Conference or Workshop Item
  9. 9

    Gene subset selection for lung cancer classification using a multi-objective strategy by Mohamad, Mohd. Saberi, Omatu, Sigeru, Deris, Safaai, Yoshioka, Michifuci

    Published 2008
    “…A microarray machine offers the ability to measure the expression levels of thousands of genes simultaneously. It is used to collect the infonnation from tissue and cell samples regarding gene expression differences that could be useful for cancer classification. …”
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    Article
  10. 10

    MRI brain tumor detection methods using contourlet transform based on time adaptive self-organizing map by Ali Farzamnia, Seyed Hamidreza Hazaveh, Seyede Safieh Siadat, Ervin Gubin Moung

    Published 2023
    “…However, when cells divide in a disorderly manner, abnormal growths can occur, forming colonies that can disrupt the normal functioning of the brain and damage healthy cells. …”
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    Article
  11. 11

    Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI) by Ganasan, Shatiskumar, Norazlianie, Sazali

    Published 2024
    “…Weka is a strong data mining and machine learning program including algorithms for data preparation, classification, regression, clustering, and visualization. …”
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    Conference or Workshop Item
  12. 12

    Decision tree-based approach for online management of PEM fuel cells for residential application by Mohd Rusllim, Mohamed

    Published 2004
    “…In this research, a Decision Tree (DT) algorithm is employed to obtain the optimal, or quasioptimal, settings of the fuel cell online and in a general framework. …”
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    Thesis
  13. 13

    Layer selection on residual network for feature extraction of pap smear images by Akbar, Alfian Hamam, Sitanggang, Imas Sukaesih, Agmalaro, Muhammad Asyhar, Haryanto, Toto, Rulaningtyas, Riries, Husin, Nor Azura

    Published 2024
    “…The data used are 4049 normal and pathological cervical cells in pap smear images sourced from SIPaKMeD, which were divided into 5 classes based on the level of cancer malignancy. …”
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    Article
  14. 14

    Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural by Saidin, Mohammad Norrish

    Published 2006
    “…The topic of this project is classification of cervical cells into normal and abnormal using 2 group discriminant analysis and neural network. …”
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    Monograph
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    Decision tree-based approach for online management of pem fuel cells for residential application by Mohamed, Mohd Rusllim

    Published 2004
    “…In this research, a Decision Tree (DT) algorithm was employed to obtain the optimal, or quasi-optimal, settings of the fuel cell online and in a general framework. …”
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    Thesis
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    Early Diagnosis of Non-small-cell lung Carcinoma from Gene Expression Using t-Distributed Stochastic Neighbor Embedding by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

    Published 2015
    “…One of the most promising techniques for early detection of cancerous cells depends on machine learning based on molecular cancer classification using gene expression profiling data. …”
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    Proceeding Paper
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    Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

    Published 2019
    “…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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    Thesis
  19. 19

    Bacterial image analysis using multi-task deep learning approaches for clinical microscopy by Chin, Shuang Yee, Jian, Dong, Khairunnisa, Hasikin, Romano, Ngui, Lai, Khin Wee, Pauline Yeoh, Shan Qing, Xiang, Wu

    Published 2024
    “…Conclusions This study has demonstrated the effectiveness, potential, and applicability of DL approaches in multi-task bacterial image analysis, focusing on automating the detection and classification of bacteria from microscopic images. The proposed models can output images with bounding boxes surrounding each detected E. coli bacteria, labelled with their growth stage and confidence level of detection. …”
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    Article
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