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  1. 1
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  2. 2
    Smart student timetable planner

    Smart student timetable planner by Wong, Xin Tong

    Published 2025
    “…Course data is managed in CSV format, parsed into JSON for fast processing, while sessionStorage and localStorage handle user data within active sessions. A Genetic Algorithm forms the core scheduling engine, generating optimized timetables that respect both hard constraints, such as avoiding clashes, and soft constraints, such as personal preferences.The final output of this project is a functional web-based timetable planner that successfully enhances scheduling efficiency, reduces the likelihood of errors, and improves the overall academic planning experience. …”
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  3. 3
    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices

    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2013
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  4. 4
    Performance evaluation of real-time multiprocessor scheduling algorithms

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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  5. 5
    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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  6. 6
    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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  7. 7
    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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  8. 8
    Route Optimization System

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
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  9. 9
    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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  10. 10
    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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  11. 11
    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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  12. 12
    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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  13. 13
    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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  14. 14
    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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  15. 15
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
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  16. 16
    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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  17. 17
    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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  18. 18
    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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  19. 19
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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  20. 20
    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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