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  1. 1
    Evaluation of feature selection algorithm for android malware detection

    Evaluation of feature selection algorithm for android malware detection by Mazlan, Nurul Hidayah, A Hamid, Isredza Rahmi

    Published 2018
    “…The Android features were filtered before detection process using TF-IDF algorithm. …”
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  2. 2
    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection

    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…Modified Binary Grey Wolf Optimiser (MBGWO) is a modern metaheuristic algorithm that has successfully been used for FS for anomaly detection. …”
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  3. 3
    Comparison of Feature Extractors for Real-Time Object Detection on Android Smartphone

    Comparison of Feature Extractors for Real-Time Object Detection on Android Smartphone by Saipullah, Khairul Muzzammil

    Published 2013
    “…As we all know, object detection algorithm is a complicated algorithm that consumes high performance hardware to execute the algorithm in real time. …”
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  4. 4
    ANALYSIS OF REAL-TIME OBJECT DETECTION METHODS FOR ANDROID SMARTPHONE

    ANALYSIS OF REAL-TIME OBJECT DETECTION METHODS FOR ANDROID SMARTPHONE by Saipullah, Khairul Muzzammil

    Published 2012
    “…As we all know, object detection algorithm is a complicated algorithm that consumes high performance hardware to execute the algorithm in real time. …”
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  5. 5
    Real-time algorithmic music composition application.

    Real-time algorithmic music composition application. by Yap, Alisa Yi Hui

    Published 2022
    “…In addition, the system also utilises JavaFx and jFugue for its graphical user interface and music programming respectively. …”
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  6. 6
    Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF)

    Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF) by Mazlan, Nurul Hidayah

    Published 2019
    “…The TF-IDF algorithm is used to filter Android features filtered before detection process. …”
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  7. 7
    Detection and extraction features for signatures images via different techniques

    Detection and extraction features for signatures images via different techniques by Fatma Susilawati, M., Alsuhimat, F.M., Iqtait, M.

    Published 2019
    “…Three techniques have been applied using (UTSig) dataset; the results showed that the BRISK algorithm got the best result among the feature detection algorithm in terms of accuracy and the FAST algorithm got the best result among the feature detection algorithm in terms of run time.…”
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  8. 8
    Optimised content-social based features for fake news detection in social media using text clustering approach

    Optimised content-social based features for fake news detection in social media using text clustering approach by Yahya, Adnan Hussein Ali

    Published 2025
    “…To address this problem, this research presents a fake news detection method that combines different features and developing methods for the most crucial phases in the detection process, including feature extraction, feature selection and fake news detection phases. …”
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  9. 9
    Application-Programming Interface (API) for Song Recognition Systems

    Application-Programming Interface (API) for Song Recognition Systems by Murtadha Arif Sahbudin, Chakib Chaouch, Salvatore Serrano

    Published 2024
    “…In addition the implementation is done by algorithm using Java’s programming language, executed through an application developed in the Android operating system. …”
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  10. 10
    A Comparative Analysis of Feature Extraction Algorithms for Augmented Reality Applications

    A Comparative Analysis of Feature Extraction Algorithms for Augmented Reality Applications by Alam, Mir Suhail, Morshidi, Malik Arman, Gunawan, Teddy Surya, Olanrewaju, Rashidah Funke

    Published 2021
    “…The quantitative results show that the ORB and SURF algorithms detect and match more features than other algorithms. …”
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  11. 11
    Enhanced feature selections of Adaboost training for face detection using genetic algorithm (GABoost)

    Enhanced feature selections of Adaboost training for face detection using genetic algorithm (GABoost) by Mohd. Zin, Zalhan, Khalid, Marzuki, Yusof, Rubiyah

    Published 2007
    “…Often some of these features are irrelevant and does not contribute directly to the face detection algorithm. …”
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  12. 12
    Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm

    Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm by Zuwairie, Ibrahim, Mohd Zaidi, Mohd Tumari, Asrul, Adam, Norrima, Mokhtar, Marizan, Mubin, Mohd Ibrahim, Shapiai

    Published 2014
    “…This study focuses on using GSA method, a new computational intelligence algorithm. Moreover, a rule-based classifier is employed to distinguish a peak point based on the selected features. …”
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  13. 13
    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…Some of the previous researchers used a feature set selection which is introduced for IDS but there still shortage in their detection rate and selected amounts of features. …”
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  14. 14
    Extremal region detection and selection with fuzzy encoding for food recognition

    Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

    Published 2019
    “…In the third algorithm, a soft assignment technique using fuzzy encoding is used to transform low-level features into a higher-level feature representation. …”
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  15. 15
    Visdom: Smart guide robot for visually impaired people

    Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

    Published 2025
    “…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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  16. 16
    Enhanced feature selections of Adaboost training for face detection using genetic algorithm

    Enhanced feature selections of Adaboost training for face detection using genetic algorithm by Mohd. Zin, Zalhan

    Published 2007
    “…With these new feature types and larger search space, Genetic Algorithm (GA) is used within the Adaboost framework, to find sets of features which can provide a better cascade of boosted classifiers with a shorter training time. …”
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  17. 17
    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System

    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

    Published 2020
    “…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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  18. 18
    Feature-based face recognition system using utilized artificial neural network

    Feature-based face recognition system using utilized artificial neural network by Chai, Tong Yuen

    Published 2010
    “…A proposed algorithm which combines RGB color map and corner detection techniques will detect the mouth corners. …”
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  19. 19
    K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm

    K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm by Al-Hafiz, Ali Raheem, Jabir, Adnan J., Subramaniam, Shamala

    Published 2025
    “…This research presents a two-phase phishing detection system by employing unsupervised feature selection and supervised classification. …”
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  20. 20
    A comparative analysis of image copy-move forgery detection algorithms based on hand and machine-crafted features

    A comparative analysis of image copy-move forgery detection algorithms based on hand and machine-crafted features by Ahmed I.T., Hammad B.T., Jamil N.

    Published 2023
    “…IC-MFD algorithms based hand-crafted features are the algorithms that detect the faked image depending on manual feature extraction while IC-MFD algorithms based machine-crafted features are the algorithms that detect the faked image automatically from image. …”
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