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  1. 1
    Intelligent home automation system for disabled people

    Intelligent home automation system for disabled people by Wan Nur Aisya Amira Wan Husni

    Published 2024
    text::Final Year Project
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  2. 2
    MotionSure: a cloud-based algorithm for detection of injected object in data in motion

    MotionSure: a cloud-based algorithm for detection of injected object in data in motion by Islam, Thouhedul, Olanrewaju, Rashidah Funke, Khalifa, Othman Omran

    Published 2017
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  3. 3
    Early Detection Of ADHD Among Children Using Machine Learning

    Early Detection Of ADHD Among Children Using Machine Learning by Nur Atiqah, Kamal

    Published 2023
    “…This abstract explores the significance of early ADHD detection, the potential of fMRI for ADHD diagnosis, and the role of machine learning in facilitating early identification. …”
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    Undergraduates Project Papers
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  4. 4
    Development of an automated detector and counter for bagworm census

    Development of an automated detector and counter for bagworm census by Ahmad, Mohd Najib

    Published 2020
    “…Color and shape features from the segmented images, combined with deep learning and Faster Region-based Convolutional Neural Networks for real time object detection showed an average detection accuracy, of 40% and 34%, at 30 cm and 50 cm camera distance, respectively. …”
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  5. 5
    Automated content sizing using accelerometer

    Automated content sizing using accelerometer by Ng, Yun Hao

    Published 2014
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  6. 6
    Automated threshold detection for object segmentation in colour image

    Automated threshold detection for object segmentation in colour image by Akhtaruzzaman, Md., Shafie, Amir Akramin, Khan, Md. Raisuddin

    Published 2016
    “…In solving this issue, this paper presents an Automated Threshold Detection Algorithm, H(•). The algorithm is applied in segmenting human lower limbs from a series of image frames of human walking. …”
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  7. 7
    Detection and Classification of Moving Objects for an Automated Surveillance System

    Detection and Classification of Moving Objects for an Automated Surveillance System by Md. Tomari, Mohd Razali

    Published 2006
    “…A completely automated system means a computer will perform the entire task from low level detection to higher level motion analysis. …”
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  8. 8
    Detection and classification of moving objects for an automated surveillance system

    Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

    Published 2006
    “…A completely automated system means a computer will perforin the entire task from low level detection to higher level motion analysis. …”
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  9. 9
    AI-Enabled Deep Learning Model for COVID-19 Identification Leveraging Internet of Things

    AI-Enabled Deep Learning Model for COVID-19 Identification Leveraging Internet of Things by Mohd Arfian, Ismail, Siti Nur Fathin Najwa, Mustaffa, Abed, Munther H.

    Published 2023
    “…This work highlights the significance of leveraging deep transfer learning and IoT in achieving early identification of suspected COVID-19 patients. …”
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  10. 10
    Detection and classification of moving objects for an automated surveillance system

    Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

    Published 2006
    “…A completely automated system means a computer will perforin the entire task from low level detection to higher level motion analysis. …”
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  11. 11
    Investigation of An Early Prediction System of Cardiac Arrest Using Machine Learning Techniques

    Investigation of An Early Prediction System of Cardiac Arrest Using Machine Learning Techniques by Muhammad Afnan, Mohammad Nasir

    Published 2022
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  12. 12
    Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues

    Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues by Aisyah, Yunus, Norfilza, Mohd Mokhtar, Raja Affendi, Raja Ali *, Siti Maryam, Ahmad Kendong, Hajar, Fauzan Ahmad

    Published 2024
    “…•Application of machine learning algorithms to the identification of potential mycobiome biomarkers for non-invasive colorectal cancer screening. …”
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  13. 13
    Analysis of banana plant health using machine learning techniques

    Analysis of banana plant health using machine learning techniques by Thiagarajan, Joshva Devadas, Kulkarni, Siddharaj Vitthal, Jadhav, Shreyas Anil, Waghe, Ayush Ashish, Raja, S.P., Rajagopal, Sivakumar, Poddar, Harshit, Subramaniam, Shamala

    Published 2024
    “…Automated systems that integrate machine learning and deep learning algorithms have proven to be effective in predicting diseases. …”
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  14. 14
    Comparative study on leaf disease identification using Yolo v4 and Yolo v7 algorithm

    Comparative study on leaf disease identification using Yolo v4 and Yolo v7 algorithm by Wang, Xinming, Tang, Sai Hong, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Mohd Idris Shah

    Published 2023
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  15. 15
    Predictive Modelling of Stroke Occurrence among Patients using Machine Learning

    Predictive Modelling of Stroke Occurrence among Patients using Machine Learning by Sures, Narayasamy, Thilagamalar, Maniam

    Published 2023
    “…Early identification of high-risk patients enables timely intervention and implementation of preventive measures, potentially reducing the burden of stroke-related complications. …”
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  16. 16
    Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga

    Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga by Mwenge , Mulenga

    Published 2022
    “…While the complex relations that exist between the microbiome and host phenotypes make machine learning algorithms suitable for analysing the microbiome data, deep learning methods are becoming more popular due to their outstanding performance in related fields. …”
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  17. 17
    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy

    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

    Published 2020
    “…Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. …”
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  18. 18
    CPG-based control system for flexible snake robot locomotion

    CPG-based control system for flexible snake robot locomotion by Khan, Md. Raisuddin, Billah, Md. Masum

    Published 2014
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  19. 19
    Comparative study of informative acoustic features for VTOL UAV faulty prediction using machine learning

    Comparative study of informative acoustic features for VTOL UAV faulty prediction using machine learning by Mohd Sani, Fareisya Zulaikha, Makhtar, Siti Noormiza, Mohd Nor, Elya, Kamarudin, Nur Diyana, Md Ali, Syaril Azrad, Md Ali, Kurnianingsih

    Published 2025
    “…Pitch, zero-crossing and short-time energy are selected as the significant audio features for the machine learning classification algorithm. UAV sounds collected in the experiment will be analysed and divided into a 60:40 ratio for training and testing datasets. …”
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  20. 20
    Design and Fabrication of Smart Home With Internet of Things Enabled Automation System

    Design and Fabrication of Smart Home With Internet of Things Enabled Automation System by Jabbar, Waheb A., Tee, Kok Kian, Roshahliza, M. Ramli, Siti Nabila, Zubir, Nurthaqifah, S. M. Zamrizaman, Balfaqih, Mohammed, Shepelev, Vladimir, Alharbi, Soltan

    Published 2019
    “…Therefore, this study presents a cost-effective and hybrid (local and remote) IoT-based home automation system with a user-friendly interface for smartphones and laptops. …”
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