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  1. 1
    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization

    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2014
    “…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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  2. 2
    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization

    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2015
    “…In this method, permission-based features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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  3. 3
    Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves

    Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves by Mat Lazim, Siti Saripa Rabiah, Sulaiman, Zulkefly, Mat Nawi, Nazmi, Mohd Mustafah, Anas

    Published 2023
    “…Thus, this study was carried out to investigate the potential application of spectroscopic technology and machine learning algorithms to classify severity level of infected trees at early stage based on spectral data. …”
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  4. 4
    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
    “…Each of the pre-processing stages and the chain coding process will be described in detail giving improvised algorithms, and examples of the processes on existing samples from the database shown. …”
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  5. 5
    Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach

    Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

    Published 2023
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  6. 6
    Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition

    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
    “…With so many algorithms developed to improve classification accuracy, interest in feature extraction in Handwritten Character Recognition (HCR) has increased. …”
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  7. 7
    Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition

    Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition by Muhammad Arif, Mohamad, Jamaludin, Sallim, Kohbalan, Moorthy

    Published 2021
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  8. 8
    Improving hand written digit recognition using hybrid feature selection algorithm

    Improving hand written digit recognition using hybrid feature selection algorithm by Wong, Khye Mun

    Published 2022
    “…The hybrid method was exemplified in a binary classification between digits ‘4’ and ‘9’ from a multiple features dataset. …”
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  9. 9
    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning

    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    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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  10. 10
    Cross-project software defect prediction

    Cross-project software defect prediction by Bala, Yahaya Zakariyau, Abdul Samat, Pathiah, Sharif, Khaironi Yatim, Manshor, Noridayu

    Published 2022
    “…Through this work, it was discovered the majority of the selected studies used machine learning techniques as classification algorithms, and 64% of the studies used the combination of Object-Oriented (OO) and Line of Code (LOC) metrics. …”
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  11. 11
    An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding

    An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

    Published 2020
    “…Performance of proposed methods surpass the classic bag of words algorithm for plant identification tasks.…”
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  12. 12
    Systematic review for phonocardiography classification based on machine learning

    Systematic review for phonocardiography classification based on machine learning by Altaf, Abdullah, Mahdin, Hairulnizam, Alive, Awais Mahmood, Ninggal, Mohd Izuan Hafez, Altaf, Abdulrehman, Javid, Irfan

    Published 2023
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  13. 13
    Phishing image spam classification research trends: Survey and open issues

    Phishing image spam classification research trends: Survey and open issues by John Abari, Ovye, Mohd Sani, Nor Fazlida, Khalid, Fatimah, Mohd Yunus Bin Sharum, Mohd Yunus, Mohd Ariffin, Noor Afiza

    Published 2020
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  14. 14
    Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq

    Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq by Uzair , Ishtiaq

    Published 2024
    “…Combining Local Binary Patterns (LBP) based texture features and deep learning features resulted in the creation of the fused features vector which was then optimized using Binary Dragonfly Algorithm (BDA) and Sine Cosine Algorithm (SCA). …”
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  15. 15
    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level

    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

    Published 2024
    thesis::doctoral thesis
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  16. 16
    Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI)

    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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  17. 17
    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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  18. 18
    Blood cell classification using deep learning

    Blood cell classification using deep learning by Liaw, Mun Kin

    Published 2022
    “…The sole objective of the continuation of this project II is to define an efficient WBC classification model from scratch. The motivation was gotten from the literature review section where various researchers developed their own methods manually through experimenting such as ensemble methods, learning algorithms, combined methodologies, etc. …”
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  19. 19
    POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD

    POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD by HENG KEOW, CHUAH

    Published 2012
    “…Simulation produces satisfactory result in identifying the disturbance and proves that it is possible to use this model for power disturbance classification even in a noisy environment. A comparative study with Probabilistic Neural Network system has proved that the proposed system is better because it needs less memory space and shorter code execution time. …”
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  20. 20
    Multi-class classification automated machine learning for predicting earthquakes using global geomagnetic field data

    Multi-class classification automated machine learning for predicting earthquakes using global geomagnetic field data by Qaedi, Kasyful, Abdullah, Mardina, Yusof, Khairul Adib, Hayakawa, Masashi, Zulhamidi, Nur Fatin Irdina

    Published 2025
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