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  1. 1
    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms

    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

    Published 2024
    “…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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  2. 2
    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…This reserarch adapted a methodology of computer vision and algorithms that exploit image segmentation, feature extraction and fuzzy classification to guide the research activities. …”
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  3. 3
    Chain coding and pre processing stages of handwritten character image file

    Chain coding and pre processing stages of handwritten character image file by Suliman, Azizah, Sulaiman, Md. Nasir, Othman, Mohamed, O. K. Rahmat, Rahmita Wirza

    Published 2010
    “…In this paper detailed descriptions of the algorithms used in the pre-processing and feature extraction phases of an offline handwritten character are discussed. …”
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  4. 4
    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC

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

    Published 2014
    “…Automated system also saves time and cost as the system is able to process large amount of image data at one time. This project 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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  5. 5
    Classification Of Cervical Cancer Stage From Pap Smear Tests

    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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  6. 6
    A new descriptor for smile classification based on cascade classifier in unconstrained scenarios

    A new descriptor for smile classification based on cascade classifier in unconstrained scenarios by Hassen, Oday Ali, Abu, Nur Azman, Zainal Abidin, Zaheera, Saad, Mohamed Darwish

    Published 2021
    “…In this paper, an adaptive model for smile classification is suggested that integrates a row-transform-based feature extraction algorithm and a cascade classifier to increase the precision of facial recognition. …”
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  7. 7
    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis

    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

    Published 2019
    “…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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  8. 8
    Development of sorting system for oil palm in vitro shoots using machine vision approach

    Development of sorting system for oil palm in vitro shoots using machine vision approach by Al-Ruhaimi, Hamdan Yahya Ahmed

    Published 2014
    “…Region-based features, namely area, centroid, aspect ratio, extent and two cropping points have been represented in the shape of OPTC in vitro shoots. By using k-means algorithm the extracted features have been evaluated. …”
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  9. 9
    Supervised neural network classifier for voice pathology

    Supervised neural network classifier for voice pathology by Murugesa Pandiyan, Paulraj, Prof. Madya Dr, Sazali, Yaacob, Prof. Dr., Sivanandam, S. N., Hariharan, Muthusamy

    Published 2011
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  10. 10
    Detection and Classification of Moving Objects for an Automated Surveillance System

    Detection and Classification of Moving Objects for an Automated Surveillance System by Md. Tomari, Mohd Razali

    Published 2006
    “…Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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  11. 11
    Detection and classification of moving objects for an automated surveillance system

    Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

    Published 2006
    “…Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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  12. 12
    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN)

    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…The data from this process were first transformed using min-max normalization and then, analysed using exploratory and descriptive analysis to discover patterns between input variables and concrete grades. Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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  13. 13
    Detection and classification of moving objects for an automated surveillance system

    Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

    Published 2006
    “…Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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  14. 14
    Analysis using data mining techniques: the exploration and review data of diabetes patients / Syarifah Adilah Mohamed Yusoff ... [et al.]

    Analysis using data mining techniques: the exploration and review data of diabetes patients / Syarifah Adilah Mohamed Yusoff ... [et al.] by Mohamed Yusoff, Syarifah Adilah, Othman, Jamal, Johan, Elly Johana, Mohd Mydin, Azlina, Wan Mohamad, Wan Anisha

    Published 2025
    “…Therefore, it is advisable for future studies to implement robust classification algorithms, such as ensemble methods, to effectively manage and extract potential insights.…”
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  15. 15
    Recommendation System Model For Decision Making in the E-Commerce Application

    Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

    Published 2024
    thesis::doctoral thesis
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  16. 16
    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui

    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

    Published 2016
    “…The use of eigenvectors decomposition (E-maps) and pre-scan methods for estimating sensitivity maps are also investigated. …”
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  17. 17
    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN)

    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…The data from this process were first transformed using min-max normalization and then, analysed using exploratory and descriptive analysis to discover patterns between input variables and concrete grades. Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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  18. 18
    Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi

    Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi by Nik Effendi, Nik Ahmad Faris

    Published 2022
    “…Besides, Artificial Neural Network (ANN) and Random Forest (RF) algorithm was used to predicted the AGB using different combination of variables. …”
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  19. 19
    Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease

    Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

    Published 2021
    “…The backscattering value of each tree was then extracted from the ALOS PALSAR-2 image. Using the Extract Multi Values tool in ArcGIS, the backscattering value for each oil palm point was derived from the processed ALOS PALSAR-2 image. …”
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  20. 20
    Enhancing Classification Algorithms with Metaheuristic Technique

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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