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  1. 1
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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  2. 2
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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  3. 3
    Hand gesture recognition for autism diagnosis using Support Vector Machine (SVM) Algorithm / Muhammad Asyraf Mohamad Zain

    Hand gesture recognition for autism diagnosis using Support Vector Machine (SVM) Algorithm / Muhammad Asyraf Mohamad Zain by Mohamad Zain, Muhammad Asyraf

    Published 2020
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  4. 4
    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification

    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

    Published 2020
    “…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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  5. 5
    The comparative study of model-based and appearance based gait recognition for leave bag behind

    The comparative study of model-based and appearance based gait recognition for leave bag behind by Zainol, Norfazilah

    Published 2018
    “…Meanwhile, the accuracy and misclassification rate (MER) of Model-based approaches obtained is 97.00% and 3.00% respectively tested on SVM classifier then the accuracy and misclassification rate (MER) of Model-based approaches is 99.00% and 1.00% respectively tested on KNN algorithm. …”
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  6. 6
    Predicting uniaxial compressive strength using Support Vector Machine algorithm

    Predicting uniaxial compressive strength using Support Vector Machine algorithm by Zakaria, Hafedz, Abdullah, Rini Asnida, Ismail, Amelia Ritahani, Amin, Mohd For

    Published 2019
    “…This paper presents the application of Support Vector Machine (SVM) algorithm to predict the UCS. An algorithm has been tested on a series of rock data using dry density and velocity parameters. …”
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  7. 7
    Multilingual Sentiment Analysis From Students Feedback: Optimal Techniques And Resources For Bengali Lingual Data

    Multilingual Sentiment Analysis From Students Feedback: Optimal Techniques And Resources For Bengali Lingual Data by Mohammad Aman Ullah

    Published 2024
    thesis::doctoral thesis
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  8. 8
    The comparative study of model-based and appearance Based gait recognition for leave bag behind

    The comparative study of model-based and appearance Based gait recognition for leave bag behind by Zainol, Norfazilah

    Published 2018
    “…Meanwhile, the accuracy and misclassification rate (MER) of Model-based approaches obtained is 97.00% and 3.00% respectively tested on SVM classifier then the accuracy and misclassification rate (MER) of Model-based approaches is 99.00% and 1.00% respectively tested on KNN algorithm. …”
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  9. 9
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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  10. 10
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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  11. 11
    Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman

    Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman by Mohd Azman, Muhammad Qayyum

    Published 2024
    “…A prototype architecture and a user-friendly graphical interface tailored for SVM-based outbreak predictions are developed, accompanied by detailed code snippets elucidating essential steps in data loading, encoding, scaling, and SVM model training. …”
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  12. 12
    SVM, ANN, and PSF modelling approaches for prediction of iron dust minimum ignition temperature (MIT) based on the synergistic effect of dispersion pressure and concentration

    SVM, ANN, and PSF modelling approaches for prediction of iron dust minimum ignition temperature (MIT) based on the synergistic effect of dispersion pressure and concentration by Arshad, U., Taqvi, S.A.A., Buang, A., Awad, A.

    Published 2021
    “…However, the SVM model with Bayesian optimizer approach can effectively assess the risk of ignition based on dust MIT under the influence of dispersion pressure and dust cloud concentration among all the approaches adopted in this study. …”
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  13. 13
    Mixed waste classification based on vision inspection / Hassan Mehmood Khan

    Mixed waste classification based on vision inspection / Hassan Mehmood Khan by Hassan Mehmood , Khan

    Published 2022
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  14. 14
    An optimal mesh algorithm for remote protein homology detection

    An optimal mesh algorithm for remote protein homology detection by M. Abdullah, Firdaus, M. Othman, Razib, Kasim, Shahreen, Hashim, Rathiah, Hassan, Rohayanti, Asmuni, Hishammuddin, Taliba, Jumail

    Published 2011
    “…Lastly, the aligned protein sequences were classified using the pHMMs generative classifier such as HMMER and SAM and also SVMs discriminative classifier such as SVM-Fold and SVM-Struct. The performances of assessed programs were evaluated using ROC, Precision and Recall tests. …”
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  15. 15
    Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak

    Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak by Abd Razak, Hana'

    Published 2020
    “…In addition Artificial Neural Network (ANN) and Support Vector Machine (SVM) are used as classifiers. Results showed the specificity and sensitivity of SVM classifier is approximately within 50% for all tested kernels. …”
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  16. 16
    Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms

    Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms by Shaharum, Nur Shafira Nisa, Mohd Shafri, Helmi Zulhaidi, Wan Ab. Karim Ghani, Wan Azlina, Samsatli, Sheila, Al-Habshi, Mohammed Mustafa, Yusuf, Badronnisa

    Published 2020
    “…However, RF extracted oil palm information better than the SVM. The algorithms were compared and the McNemar's test showed significant values for comparisons between SVM and CART and RF and CART. …”
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  17. 17
    Enhancement on image face recognition using Hybrid Multiclass SVM (HM-SVM)

    Enhancement on image face recognition using Hybrid Multiclass SVM (HM-SVM) by Selamat, M.H., Rais, H.M.

    Published 2016
    “…The accuracy evaluation of this research was based on two different SVM kernel. Besides, the research was performed based on Orthogonal Wavelet families. …”
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  18. 18
    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
    “…SVM-RFE could further select the subset features based on ranking weights criterion, insignificant features with small ranking weights will be removed while retaining only significant features that have greater influence. …”
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  19. 19
    A Hybrid of Functional Networks and Support Vector Machine Models for the Prediction of Petroleum Reservoir Properties

    A Hybrid of Functional Networks and Support Vector Machine Models for the Prediction of Petroleum Reservoir Properties by Fatai Adesina, Anifowose, Jane, Labadin, Abdulazeez, Abdulraheem

    Published 2011
    “…This proposed FNSVM hybrid model benefits from the excellent performance of the least-square-based model-selection algorithm of Functional Networks and the non-linear high-dimensional feature transformation capability that is based on structural risk minimization and Tikhonov regularization properties of SVM. …”
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    Proceeding
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  20. 20
    Dual-tone multifrequency signal detection using support vector machines

    Dual-tone multifrequency signal detection using support vector machines by Nagi J., Tiong S.K., Yap K.S., Ahmed S.K.

    Published 2023
    Subjects:
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