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  1. 1
    The classification of wink-based eeg signals by means of transfer learning models

    The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

    Published 2021
    “…The utilization of deep learning, particularly Transfer Learning (TL), have been demonstrated in the literature to b e able to provide seamless extraction of such signals in a myria d of various applications. …”
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  2. 2
    Mobility-aware Offloading Decision For Multi-access Edge Computing In 5g Networks

    Mobility-aware Offloading Decision For Multi-access Edge Computing In 5g Networks by Saeid Jahandar, Lida Kouhalvandi, Ibraheem Shayea, Mustafa Ergen, Marwan Hadri Azmi, Hafizal Mohamad

    Published 2024
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  3. 3
    A framework of modified adaptive neuro-fuzzy inference engine

    A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

    Published 2012
    “…The performance of MANFIE was compared with existing methods in a diversity of practical benchmark applications such as pattern classifications, time series predictions, modeling with inverse learning control and mobile robot navigation. …”
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  4. 4
    Location-Based Approach for Route Maintenance in Dynamic Source Routing Protocol

    Location-Based Approach for Route Maintenance in Dynamic Source Routing Protocol by Sjaugi, Muhammad Farhan

    Published 2008
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  5. 5
    The Classification of Wink-Based EEG Signals: The identification on efficiency of transfer learning models by means of kNN classifier

    The Classification of Wink-Based EEG Signals: The identification on efficiency of transfer learning models by means of kNN classifier by Jothi Letchumy, Mahendra Kumar, Mamunur, Rashid, Rabiu Muazu, Musa, Mohd Azraai, Mohd Razman, Norizam, Sulaiman, Rozita, Jailani, Anwar, P. P. Abdul Majeed

    Published 2021
    “…The validation and testing CA attained through NasNetMobile and NasNetLarge models are 100%. Therefore, it could be concluded that the proposed pipeline which consists of CWT-NasNetLarge-kNN is suitable to be adopted to classify wink-based EEG signals for different BCI applications.…”
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  6. 6
    A real-time mobile notification system for inventory stock out detection using SIFT and RANSAC

    A real-time mobile notification system for inventory stock out detection using SIFT and RANSAC by Merrad, Yacine, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Gunawan, Teddy Surya

    Published 2020
    “…The proposed method is a machine learning based real-time notification system using the exciting Scale Invariant Feature Transform feature detector (SIFT) and Random Sample Consensus (RANSAC) algorithms. …”
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  7. 7
    Mobile tour guide application with attraction recognition for UTAR Kampar campus

    Mobile tour guide application with attraction recognition for UTAR Kampar campus by Lee, Mun Hong

    Published 2021
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  8. 8
    Mobile application for real time baby sign language recognition using YOLOv8 / Siti Aishah Idris and Ahmad Firdaus Ahmad Fadzil

    Mobile application for real time baby sign language recognition using YOLOv8 / Siti Aishah Idris and Ahmad Firdaus Ahmad Fadzil by Idris, Siti Aishah, Ahmad Fadzil, Ahmad Firdaus

    Published 2024
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  9. 9
    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
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  10. 10
    Framework for stream clustering of trajectories based on temporal micro clustering technique

    Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

    Published 2018
    “…In the online phase, the stream clustering algorithm for trajectories based on the lifespan of the cluster is proposed (CC_TRS) to overcome the limitations of the time window technique. …”
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  11. 11
    Machine learning approach for tenaga nasional berhad (tnb) overhead powerline and electricity pole inventory using mobile laser scanning data

    Machine learning approach for tenaga nasional berhad (tnb) overhead powerline and electricity pole inventory using mobile laser scanning data by Mohd Rapheal M.S.A., Farhana A., Mohd Salleh M.R., Abd Rahman M.Z., Majid Z., Musliman I.A., Abdullah A.F., Abd Latif Z.

    Published 2023
    “…Decision trees; Laser applications; Learning algorithms; Machine learning; Mean square error; Scanning; Classifieds; Electricity assets; Electricity pole; Laser scanner data; Laserscanners; Machine-learning; Mobile laser scanner; Overhead powerline; Point-clouds; Power lines; Poles…”
    Conference Paper
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  12. 12
    An Education-Based System for Two-Way Translations of Sign Language

    An Education-Based System for Two-Way Translations of Sign Language by Muhammad Faiz Aiman, Che Umar, Hock Tze, Wong@ Farrah Wong, Sariah, Abang, Jamal, Ahmad Dargham, Seng Kheau, Chung, Mazlina, Mamat

    Published 2025
    “…The model's performance is assessed, achieving 97.3% accuracy within 12 trials through Android mobile applications. The model exhibits occasional misclassifications, primarily for certain hand orientations, such as 'I', 'N', 'E', and 'S'. …”
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  13. 13
    Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches

    Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches by Al Mahmud, Suaib, Kamarulariffin, Abdurrahman, Mohd Ibrahim, Azhar, Haja Mohideen, Ahmad Jazlan

    Published 2024
    “…In this review paper, a comprehensive review of mobile robot navigation algorithms has been conducted. …”
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  14. 14
    GuitarApprentice: A Mobile Application for Acoustic Guitar Learning using Fast Fourier Transform algorithm

    GuitarApprentice: A Mobile Application for Acoustic Guitar Learning using Fast Fourier Transform algorithm by Lau , Jason Kim Wee

    Published 2013
    “…The objective of the project is to create a learning-based mobile application for learning to play an acoustic guitar. …”
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  15. 15
    Algorithm visualization design guidelines for mobile leaning

    Algorithm visualization design guidelines for mobile leaning by Supli, Ahmad Affandi, Shiratuddin, Norshuhada

    Published 2018
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  16. 16
    A new mobile botnet classification based on permission and API calls

    A new mobile botnet classification based on permission and API calls by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

    Published 2024
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  17. 17
    Bacterial image analysis using multi-task deep learning approaches for clinical microscopy

    Bacterial image analysis using multi-task deep learning approaches for clinical microscopy by Chin, Shuang Yee, Jian, Dong, Khairunnisa, Hasikin, Romano, Ngui, Lai, Khin Wee, Pauline Yeoh, Shan Qing, Xiang, Wu

    Published 2024
    “…Methods Three object detection networks of DL algorithms, namely SSD-MobileNetV2, EfficientDet, and YOLOv4, were developed to automatically detect Escherichia coli (E. coli) bacteria from microscopic images. …”
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  18. 18
    Review on ubiquitous education system with multi-agent synchronization on mobile learning application environment

    Review on ubiquitous education system with multi-agent synchronization on mobile learning application environment by Mwinyi, Amir Kombo, Syed Mohamed, Syed Abdul Rahman Al Haddad, Abdullah, Rusli, Hashim, Shaiful Jahari

    Published 2012
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  19. 19
    Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin

    Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin by Husam , N. S. Yasin

    Published 2021
    “…The computation time complexity of the Q-Learning-based test coverage algorithm was also analyzed. …”
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  20. 20
    A New Mobile Botnet Classification based on Permission and API Calls

    A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

    Published 2024
    “…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. …”
    Proceedings Paper
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