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  1. 1
    Dynamic android malware category classification using semi-supervised deep learning

    Dynamic android malware category classification using semi-supervised deep learning by Mahdavifar, Samaneh, Kadir, Andi Fitriah Abdul, Fatemi, Rasool, Alhadidi, Dima, Ghorbani, Ali A

    Published 2020
    “…Despite the academic and industrial attempts, devising a robust and efficient solution for Android malware detection and category classification is still an open problem. Supervised machine learning has been used to solve this issue. …”
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    Proceeding Paper
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  2. 2
    Performances of machine learning algorithms for binary classification of network anomaly detection system

    Performances of machine learning algorithms for binary classification of network anomaly detection system by Nawir, M., Amir, A., Lynn, O.B., Yaakob, N., Ahmad, R.B.

    Published 2018
    “…Several issues regarding these available labelled network datasets are discussed in this paper. …”
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  3. 3
    Real-time classification improvement of Indonesian sign system letters (SIBI) using K-Nearest Neighbor algorithm

    Real-time classification improvement of Indonesian sign system letters (SIBI) using K-Nearest Neighbor algorithm by Dhewa, Oktaf Agni, Utama, Safitri Yuliana, Nasuha, Aris, Gunawan, Teddy Surya, Pratama, Gilang Nugraha Putu

    Published 2024
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  4. 4
    The classification of FTIR plastic bag spectra via label spreading and stacking

    The classification of FTIR plastic bag spectra via label spreading and stacking by Almanifi, Omair Rashed Abdulwareth, Ng, Jee Kwan, Anwar P. P., Abdul Majeed

    Published 2021
    “…Utilising machine learning as a method of filling the mentioned issue is suggested by this paper. Four pipelines were investigated, consisting of two machine learning algorithms, a stacked model that stacks the KNN, SVM and RF algorithms together, and Label spreading, as well as two different dimensionality reduction methods namely; SVD and UMAP. …”
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  5. 5
    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd

    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

    Published 2022
    “…The study verified that the FID3-DBD algorithm could classify the continuous data, and the BFID3-DBD algorithm overcame the overfitting issue, reduced high variance, and increased test data classification accuracy.…”
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  6. 6
    Classification of JPEG files by using extreme learning machine

    Classification of JPEG files by using extreme learning machine by Ali, Rabei Raad, Mohamad, Kamaruddin Malik, Jamel, Sapiee, Ahmad Khalid, Shamsul Kamal

    Published 2018
    “…This paper proposes an Extreme Learning Machine (ELM) algorithm to assign a class label of JPEG or Non-JPEG image for files in a continuous series of data clusters. …”
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  7. 7
    Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling

    Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

    Published 2023
    Conference Paper
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  8. 8
    Object-Oriented Programming semantics representation utilizing agents

    Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

    Published 2011
    “…Novices tend to refer to source codes examples and adapt the source codes to the problem given in their assignments. …”
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  9. 9
    Scene classification for aerial images based on CNN using sparse coding technique

    Scene classification for aerial images based on CNN using sparse coding technique by Qayyum, A., Malik, A.S., Saad, N.M., Iqbal, M., Faris Abdullah, M., Rasheed, W., Rashid Abdullah, T.A., Bin Jafaar, M.Y.

    Published 2017
    “…Recent developments include several approaches and numerous algorithms address the task. This article proposes a convolutional neural network (CNN) approach that utilizes sparse coding for scene classification applicable for HRRS unmanned aerial vehicle (UAV) and satellite imagery. …”
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  10. 10
    Transfer Learning for Lung Nodules Classification with CNN and Random Forest

    Transfer Learning for Lung Nodules Classification with CNN and Random Forest by Abdulrazak, Saleh, Chee, Ka Chin, Ros Ameera, Rosdi

    Published 2023
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  11. 11
    Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling

    Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling by Zulaiha Ali Othman, Afaf Muftah Adabashi, Suhaila Zainudin, Saadat M. Al Hashmi

    Published 2011
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  12. 12
    Maldroid- attribute selection analysis for malware classification

    Maldroid- attribute selection analysis for malware classification by Rahiwan Nazar, Romli, Mohamad Fadli, Zolkipli, Mohd Zamri, Osman

    Published 2019
    “…Hence, the objective of this paper is to find the most effective and efficient attribute selection and classification algorithm in malware detection. Moreover, in order to get the best combination between attribute selection and classification algorithm, eight attributes selection and seven categories machine learning algorithm are applied in this study. …”
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  13. 13
    Scene classification for aerial images based on CNN using sparse coding technique

    Scene classification for aerial images based on CNN using sparse coding technique by Qayyum A., Malik A.S., Saad N.M., Iqbal M., Faris Abdullah M., Rasheed W., Rashid Abdullah T.A., Bin Jafaar M.Y.

    Published 2023
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  14. 14
    Transfer Learning for Lung Nodules Classification with CNN and Random Forest

    Transfer Learning for Lung Nodules Classification with CNN and Random Forest by Abdulrazak Yahya, Saleh, Chee, Ka Chin, Ros Ameera, Rosdi

    Published 2024
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  15. 15
    A comparative study in classification techniques for unsupervised record linkage model

    A comparative study in classification techniques for unsupervised record linkage model by Ektefa, Mohammadreza, Sidi, Fatimah, Ibrahim, Hamidah, A. Jabar, Marzanah, Memar, Sara

    Published 2011
    “…In order to utilize the supervised classification algorithms without consuming a lot of time for labeling data manually, a two step method which selects the training data automatically has been proposed in previous studies. …”
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  16. 16
    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm

    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm by Ali, M., Jung, L.T., Abdel-Aty, A.-H., Abubakar, M.Y., Elhoseny, M., Ali, I.

    Published 2020
    “…The k-NN algorithm is one of the most renowned ML algorithms widely used in the area of data classification research. …”
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  17. 17
    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm

    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm by Ali, M., Jung, L.T., Abdel-Aty, A.-H., Abubakar, M.Y., Elhoseny, M., Ali, I.

    Published 2020
    “…The k-NN algorithm is one of the most renowned ML algorithms widely used in the area of data classification research. …”
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  18. 18
    A hierarchical deep convolutional neural network for asphalt pavement crack detection and classification / Nor Aizam Muhamed Yusof

    A hierarchical deep convolutional neural network for asphalt pavement crack detection and classification / Nor Aizam Muhamed Yusof by Muhamed Yusof, Nor Aizam

    Published 2021
    “…The CrackLabel utilises a special design image thresholding algorithm known as Global and Lower Quartile Average Intensity (GLQAI). …”
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    Thesis
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  19. 19
    Boosting and bagging classification for computer science journal

    Boosting and bagging classification for computer science journal by Wibawa, Aji Prasetya, Putri, Nastiti Susetyo Fanany, Al Rasyid, Harits, Nafalski, Andrew, Hashim, Ummi Rabaah

    Published 2023
    “…Therefore, a method of categorization is provided to solve this issue. Classification is a machine-learning technique that groups data based on the supplied label class. …”
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  20. 20
    Development of vehicle counting system by using background subtraction technique / Muhammad Fadhli Md Azemin

    Development of vehicle counting system by using background subtraction technique / Muhammad Fadhli Md Azemin by Md Azemin, Muhammad Fadhli

    Published 2018
    “…Vehicle classification and counting has been voice require issue of intelligent traffic control system (ITS). …”
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