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  1. 1
    DEVELOPMENT OF DRIVER DROWSINESS DETECTION ALGORITHM

    DEVELOPMENT OF DRIVER DROWSINESS DETECTION ALGORITHM by YVONNE, PHUA YEE WUN

    Published 2022
    “…The second approach applies deep learning methods with three different convolution neural network models, which are modified LeNet-5, MobileNet-V2, and DenseNet-201 to detect drowsiness. …”
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    Final Year Project Report / IMRAD
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  2. 2
    Automated visual defect detection using deep learning

    Automated visual defect detection using deep learning by Loh, Xiao

    Published 2022
    “…The main goal of this project is to study and develop various automated defect detection models by utilizing state-of-the-art deep learning segmentation algorithms, including U-Net, Double U-Net, SETR, TransU-Net, TransDAU-Net, CAM and SEAM to perform semantic segmentation in fully supervised and weakly supervised learning manners. …”
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    Final Year Project / Dissertation / Thesis
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  3. 3
    Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications

    Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications by Teoh, Ming Xue

    Published 2025
    “…In recent studies, we seen developers and researchers proposing solutions on deep learning algorithms like YOLO, EfficientNet, CNN, MobileNet etc. …”
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    Final Year Project / Dissertation / Thesis
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  4. 4
    Mobile Learning: An Application Prototype for AVL Tree Learning Object

    Mobile Learning: An Application Prototype for AVL Tree Learning Object by Ibrahim, Mohammad Noor, Mahamad, Saipunidzam, Chua, Edrea Ning Wei

    Published 2010
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    Article
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  5. 5
    Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza

    Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza by Ghulam , Murtaza

    Published 2021
    “…For BrC detection, an efficient and reliable model namely Ensemble BrC Detection Network (EBrC-Net) and three misclassification reduction (McR) algorithms are developed. …”
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    Thesis
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  6. 6
    Mobile machine vision for railway surveillance system using deep learning algorithm

    Mobile machine vision for railway surveillance system using deep learning algorithm by Kit, Guan Lim, Daniel Siruno, Min, Keng Tan, Chung, Fan Liau, Sha, Huang, Tze, Kenneth Kin Teo

    Published 2021
    “…In this paper, object detection model is developed and implemented with deep learning algorithm. …”
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    Proceedings
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  7. 7
    ReSTiNet: An efficient deep learning approach to improve human detection accuracy

    ReSTiNet: An efficient deep learning approach to improve human detection accuracy by Shahriar Shakir, Sumi, Dayang Rohaya, Awang Rambli, Mirjalili, Seyedali, Miah, M. Saef Ullah, Muhammad Mudassir, Ejaz

    Published 2023
    “… • All the necessary steps, algorithms, and mathematical formulas for building the net- work are provided…”
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  8. 8
    Lexicon-based and immune system based learning methods in Twitter sentiment analysis

    Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

    Published 2016
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    Conference or Workshop Item
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  9. 9
    ReSTiNet : An efficient deep learning approach to improve human detection accuracy

    ReSTiNet : An efficient deep learning approach to improve human detection accuracy by Sumit, Shahriar Shakir, Dayang Rohaya, Awang Rambli, Seyedali, Mirjalili, Miah, Md Saef Ullah, Muhammad Mudassir, Ejaz

    Published 2023
    “…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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  10. 10
    ReSTiNet: An Efficient Deep Learning Approach to Improve Human Detection Accuracy

    ReSTiNet: An Efficient Deep Learning Approach to Improve Human Detection Accuracy by Sumit, S.S., Rambli, D.R.A., Mirjalili, S., Miah, M.S.U., Ejaz, M.M.

    Published 2023
    “…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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  11. 11
    Object detection and classification in marine ecosystem using deep learning neural network / Muhammad Afiq Azman

    Object detection and classification in marine ecosystem using deep learning neural network / Muhammad Afiq Azman by Azman, Muhammad Afiq

    Published 2025
    “…The primary objective is to develop and implement artificial intelligence (AI) and machine learning (ML) algorithms tailored to effectively identify within marine ecosystems. …”
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    Student Project
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  12. 12
    Evaluation of the Transfer Learning Models in Wafer Defects Classification

    Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

    Published 2022
    “…Transfer Learning is one of the common methods. Various algorithms under Transfer Learning had been developed for different applications. …”
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  13. 13
    Classification model for chlorophyll content using CNN and aerial images

    Classification model for chlorophyll content using CNN and aerial images by Wagimin, Mohd Nazuan, Ismail, Mohammad Hafiz, Mohd Fauzi, Shukor Sanim, Seng, Chuah Tse, Abd Latif, Zulkiflee, Muharam, Farrah Melissa, Mohd Zaki, Nurul Ain

    Published 2024
    “…The classification model in this study used transfer learning algorithms, which were InceptionV3, DenseNet121 and ResNet50, with the canopyscale level of mango plant RGB images with complex leaf structures in an uncontrolled and open area. …”
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  14. 14
    Deep learning segmentation of brain ischemic lesion from magnetic resonance images for three-dimensional modelling

    Deep learning segmentation of brain ischemic lesion from magnetic resonance images for three-dimensional modelling by Muhammad Ismaill, Mat Lizah, Nasrul Hadi, Johari, Mohd Jamil, Mohamed Mokhtarudin

    Published 2025
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  15. 15
    A Novel Hybrid Unet-RBF and CNN-RBF Algorithm for Autism Spectrum Disorder Classification

    A Novel Hybrid Unet-RBF and CNN-RBF Algorithm for Autism Spectrum Disorder Classification by Lim, Huey Chern, Abdulrazak Yahya, Saleh

    Published 2024
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  16. 16
    Deep learning-based water segmentation for autonomous surface vessel

    Deep learning-based water segmentation for autonomous surface vessel by Mohd Adam, Muhammad Ammar, Ibrahim, Ahmad Imran, Zainal Abidin, Zulkifli, Mohd Zaki, Hasan Firdaus

    Published 2020
    “…In purpose of benchmarking models, Fully Convolutional Network (FCN), SegNet and U-Net are trained on a publicly available dataset, IntCatch Vision Data Set (ICVDS), to evaluate the performance. …”
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    Proceeding Paper
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  17. 17
    Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification

    Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification by Huey Chern, Lim

    Published 2024
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    Thesis
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  18. 18
    Leveraging CQT-VMD and pre-trained AlexNet architecture for accurate pulmonary disease classification from lung sound signals

    Leveraging CQT-VMD and pre-trained AlexNet architecture for accurate pulmonary disease classification from lung sound signals by Neili, Zakaria, Sundaraj, Kenneth

    Published 2025
    “…The results, showing high accuracy, a sensitivity of 91.21%, and a specificity of 94.9%, highlight the robustness and effectiveness of the proposed method, paving the way for its clinical adoption and the development of lightweight deep-learning algorithms for portable diagnostic tools.…”
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  19. 19
    Classification of brain tumors: using deep transfer learning

    Classification of brain tumors: using deep transfer learning by Husin, Nor Azura, Husam, Mohamed, Hussin, Masnida

    Published 2023
    “…To achieve the goal, a modified GoogleNet model was used. Various learning algorithms were tested. …”
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  20. 20
    A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification

    A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification by Madanan M., Gunasekaran S.S., Mahmoud M.A.

    Published 2024
    Conference Paper
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