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  1. 1
    A malware analysis and detection system for mobile devices / Ali Feizollah

    A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

    Published 2017
    “…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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  2. 2
    Development Of Machine Learning User Interface For Pump Diagnostics

    Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

    Published 2022
    “…The data collected for this machine learning model is using the statistically significant features from vibration and acoustic analysis. The features extracted of time domain and frequency domain in vibration and acoustic will use as database of a Support Vector Machine (SVM) algorithms by using MATLAB R2021a. …”
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  3. 3
    Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali

    Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali by Mohd Razali, Ainaa Farhanah

    Published 2022
    “…The study of areal surface metrology analysis focuses on feature identification to assist feature extraction procedure is crucial since it will help to enhance the essential features found on the surface. …”
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  4. 4
    Feature Extraction Algorithms of Retinal Microvasculature for Cost-Effective Medical Device

    Feature Extraction Algorithms of Retinal Microvasculature for Cost-Effective Medical Device by Kuryati, Kipli, Mohammed Enamul, Hoque, Lim, Lik Thai, Hamdi, M.M.

    Published 2019
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  5. 5
    Optimising acoustic features for source mobile device identification using spectral analysis techniques / Mehdi Jahanirad

    Optimising acoustic features for source mobile device identification using spectral analysis techniques / Mehdi Jahanirad by Mehdi , Jahanirad

    Published 2016
    “…Hence, addressing robust feature extraction methods for source communication device identification is necessary. …”
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  6. 6
    Designing an expressive virtual Kompang on mobile device with tri-axial accelerometer

    Designing an expressive virtual Kompang on mobile device with tri-axial accelerometer by Leng, Hoo Yong, Mohd Norowi, Noris, Jantan, Azrul Hazri

    Published 2018
    “…Multiple features related to the shape of the drum hit are extracted by using tri-axis accelerometer sensors of the mobile device. …”
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  7. 7
    Novel CE-CBCE feature extraction method for object classification using a low-density LiDAR point cloud

    Novel CE-CBCE feature extraction method for object classification using a low-density LiDAR point cloud by Mohd Romlay, Muhammad Rabani, Mohd Ibrahim, Azhar, Toha, Siti Fauziah, De Wilde, Philippe, Venkat, Ibrahim

    Published 2021
    “…Low-end LiDAR sensor provides an alternative for depth measurement and object recognition for lightweight devices. However due to low computing capacity, complicated algorithms are incompatible to be performed on the device, with sparse information further limits the feature available for extraction. …”
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  8. 8
    Feature extraction: hand shape, hand position and hand trajectory path

    Feature extraction: hand shape, hand position and hand trajectory path by Bilal, Sara Mohammed Osman Saleh, Akmeliawati, Rini

    Published 2011
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  9. 9
    Development of an intelligent multimodal biometric system for household appliances control

    Development of an intelligent multimodal biometric system for household appliances control by Abiodun musa, Aibinu

    Published 2012
    “…In the first phase, individual biometrics recognition algorithms were developed for each biometrics feature. …”
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  10. 10
    Deep Learning-Based Geomagnetic Navigation Method Integrated with Dead Reckoning

    Deep Learning-Based Geomagnetic Navigation Method Integrated with Dead Reckoning by Yan, Suqing, Su, Yalan, Luo, Xiaonan, Sun, Anqing, Ji, Yuanfa, Kamarul Hawari, Ghazali

    Published 2023
    “…First, a multidimensional geomagnetic feature extraction method is presented which can extract magnetic features from spatial and temporal aspects. …”
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  11. 11
    Algorithm of local features fusion and modified covariance-matrix technique for hand motion position estimation and hand gesture trajectory tracking approach

    Algorithm of local features fusion and modified covariance-matrix technique for hand motion position estimation and hand gesture trajectory tracking approach by Thabet, Eman, Khalid, Fatimah, Sulaiman, Puteri Suhaiza, Yaakob, Razali

    Published 2020
    “…Hence, to tackle these difficulties and extract gesture features for gesture recognition phase accurately, this paper proposed an algorithm of dynamic hand trajectory tracking for gesture recognition. …”
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  12. 12
    Comparison Of Ridge Filters Performance in Human Vein Extraction Using 850nm Near Infrared Led Illumination

    Comparison Of Ridge Filters Performance in Human Vein Extraction Using 850nm Near Infrared Led Illumination by Abu Bakar Abd Rahman, Abdullah Bade, Fuei, Pien Chee

    Published 2023
    “…This paper investigates the performance of the ridge filters algorithm for vein feature extraction by using the NIR imaging technique to visualise human vein vessels. …”
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  13. 13
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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  14. 14
    “Analysis of EEG Recordings During Grasp and Lift (GAL) Trials

    “Analysis of EEG Recordings During Grasp and Lift (GAL) Trials by Musa, Huwaida

    Published 2018
    “…There are two types of investigation which are classification with feature extraction and without feature extraction. …”
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  15. 15
    Classification of hand gestures from EMG signals / Diaa Albitar

    Classification of hand gestures from EMG signals / Diaa Albitar by Albitar, Diaa

    Published 2022
    “…There are two hundred forty-eight features that are extracted from time domain and the frequency domain. …”
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  16. 16
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  17. 17
    Anomaly detection in system log files using machine learning algorithms / Zahedeh Zamanian

    Anomaly detection in system log files using machine learning algorithms / Zahedeh Zamanian by Zahedeh, Zamanian

    Published 2019
    “…This study uses principal component analysis (PCA) as a feature extraction method to extract 117 independent and discriminative features with 95% of variance. …”
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  18. 18
    Data mining in mobile ECG based biometric identification

    Data mining in mobile ECG based biometric identification by Sidek, Khairul Azami, Mai, Vu, Khalil, Ibrahim

    Published 2014
    “…Subjects in MIT-BIH Normal Sinus Rhythm Database (NSRDB) were used to validate the reliability and stability of the subject recognition methods. Discriminatory features extracted from the experimentation were later applied to different classifiers for performance measures based on the complexity of our proposed sample extraction method when compared to other related algorithms, the total execution time (TET) applied on different classifiers in various mobile devices and the classification accuracies when applied to various classification techniques. …”
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  19. 19
    Provider independent cryptographic tools

    Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

    Published 2003
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  20. 20
    Brain Machine Interface Controlled Robot Chair

    Brain Machine Interface Controlled Robot Chair by Hema Chengalvarayan, Radhakrishnamurthy

    Published 2010
    “…Mu, Beta and Gamma frequency bands related to the motor actions are extracted using customised filters. New features based on time and frequency components of the EEG signals are proposed and tested with classifiers. …”
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