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    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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    Article
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    DEVELOPMENT OF DRIVER DROWSINESS DETECTION ALGORITHM by YVONNE, PHUA YEE WUN

    Published 2022
    “…To contribute to the existing works of driver drowsiness detection systems, this project aims to develop a more useful drowsiness detection algorithm with low complexity and high performance using Python 3.10.1 software. …”
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    Final Year Project Report / IMRAD
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    Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza by Ghulam , Murtaza

    Published 2021
    “…BreakHis is a large and complex dataset (i.e., four subtypes of each benign and malignant BrTs) that publicly available. 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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    Efficient Malware Detection And Response Model Using Enhanced Parallel Deep Learning (EPDL-MDR) by Chowdhury Sajadul Islam

    Published 2026
    “…The final EPDL model gained 99.00% accuracy, outperforming five benchmark models (EfficientNetB2, MobileNetV2, RegNet, ResNet50, and SwinTransformer). …”
    thesis::doctoral thesis
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    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 validation of the proposed ReSTiNet model has been done on INRIA person dataset using the Tesla K80. â�¢ All the necessary steps, algorithms, and mathematical formulas for building the net- work are provided. â�¢ The network is small in size but has a faster detection speed with high accuracy. …”
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    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 validation of the proposed ReSTiNet model has been done on INRIA person dataset using the Tesla K80. • All the necessary steps, algorithms, and mathematical formulas for building the net- work are provided. • The network is small in size but has a faster detection speed with high accuracy.…”
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    Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine by Fathi Mahdi Elsiddig Haroun, Mr.

    Published 2023
    “…The SVM algorithm has been used to detect high- and low-density vegetation regions from the extracted ROI. …”
    text::Thesis
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    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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    Paddy Plant (Oryza Sativa) Disease Detection Based On Improved Convolution Neural Network by Marceila Suzie, Ambrose

    Published 2023
    “…Some existing methods, for example, GoogleNet, InceptionNet and VGGNet are used to detect paddy diseases. …”
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    Final Year Project Report / IMRAD
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    AUTONOMOUS POWER LINE INSPECTION USING COMPUTER VISION by LAW, JIN MING

    Published 2022
    “…An algorithm with DenseNet-201 backbone consisting of two branches which are class label classification and bounding box regression is developed. …”
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    Final Year Project Report / IMRAD
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    Comparative analysis of deepfake image detection method using VGG16, VGG19 and ResNet50 by Ashani, Zahra Nazemi, Che Ilias, Iszuanie Syfidza, Ng, Keng Yap, Kamel Ariffin, Muhammad Rezal, Jarno, Ahmad Dahari, Zamri, Nor Zarina

    Published 2024
    “…In this study, we explore the application of AI for deepfake image detection. Specifically, we focus on three convolutional neural network (CNN) algorithms—VGG16, VGG19, and ResNet—for this purpose. …”
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