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  1. 1
    On the combination of adaptive neuro-fuzzy inference system and deep residual network for improving detection rates on intrusion detection

    On the combination of adaptive neuro-fuzzy inference system and deep residual network for improving detection rates on intrusion detection by Jia, Liu, Yin Chai, Wang, Chee Siong, Teh, Xinjin, Li, Liping, Zhao, Fengrui, Wei

    Published 2022
    “…Also, the performance of the proposed method is compared with the original ResNet algorithm and other deep learning-based and ANFIS-based methods. …”
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  2. 2
    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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  3. 3
    Application of Fuzzy C-Means with YCbCr and DenseNet-201 for Automated Corn Leaf Disease Detection

    Application of Fuzzy C-Means with YCbCr and DenseNet-201 for Automated Corn Leaf Disease Detection by Chyntia Jaby, Entuni

    Published 2021
    “…This is due to instability and complexity of the network. Hence, algorithm that performed better is required. Thus, in this study, image segmentation method of Fuzzy C-Means with YCbCr and image classification method of DenseNet-201 to detect plant leaf diseases is proposed. …”
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  4. 4
    Multi-method diagnosis of CT images for rapid detection of intracranial hemorrhages based on deep and hybrid learning

    Multi-method diagnosis of CT images for rapid detection of intracranial hemorrhages based on deep and hybrid learning by Mohammed, Badiea Abdulkarem, Senan, Ebrahim Mohammed, Al-Mekhlafi, Zeyad Ghaleb, Rassem, Taha Hussein, Makbol, Nasrin M., Alanazi, Adwan Alownie, Almurayziq, Tariq S., Ghaleb, Fuad A., Sallam, Amer A.

    Published 2022
    “…The third proposed system uses artificial neural networks (ANNs) based on the features of the GoogLeNet, ResNet-50 and AlexNet models, whose dimensions are reduced by a principal component analysis (PCA) algorithm, and then the low-dimensional features are combined with the features of the GLCM and LBP algorithms. …”
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  5. 5
    Automated QT interval measurement using modified Pan-Tompkins algorithm with independent isoelectric line approach

    Automated QT interval measurement using modified Pan-Tompkins algorithm with independent isoelectric line approach by Jumahat, Shaliza, Gan, Kok Beng, Misran, Norbahiah, Islam, Mohammad Tariqul, Mahri, Nurhafizah, Ja'afar, Mohd. Hasni

    Published 2020
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  6. 6
    Comparative analysis of deepfake image detection method using VGG16, VGG19 and ResNet50

    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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  7. 7
    Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine

    Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine by Fathi Mahdi Elsiddig Haroun, Mr.

    Published 2023
    “…In this dissertation, a new vegetation encroachment detection method was proposed by studying the feasibility of using the visible-light band of highresolution satellite images using the RetinaNet deep learning model and Support Vector Machine algorithm (SVM). …”
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  8. 8
    Detection and Monitoring of Power Line Corridor from Satellite Imagery Using RetinaNet and K-Mean Clustering

    Detection and Monitoring of Power Line Corridor from Satellite Imagery Using RetinaNet and K-Mean Clustering by Haroun F.M.E., Deros S.N.M., Din N.M.

    Published 2023
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  9. 9
    Analysis of detection system for cover tape offset in the tap and reel process using neural net time series method

    Analysis of detection system for cover tape offset in the tap and reel process using neural net time series method by Khamil, Khairun Nisa, Rosli, Muhammad Irfan, Sulaiman, Siti Fatimah, Mohd Chachuli, Siti Amaniah, Isa, Ahmad Nizam

    Published 2025
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  10. 10
    Features selection for IDS in encrypted traffic using genetic algorithm

    Features selection for IDS in encrypted traffic using genetic algorithm by Barati, Mehdi, Abdullah, Azizol, Mahmod, Ramlan, Mustapha, Norwati, Udzir, Nur Izura

    Published 2013
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  11. 11
    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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  12. 12
    Classification and detection of intelligent house resident activities using multiagent

    Classification and detection of intelligent house resident activities using multiagent by ,, Mohd. Marufuzzaman, M. B. I., Raez, M. A. M., Ali, Rahman, Labonnah F.

    Published 2013
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  13. 13
    A multi-nets ANN model for real-time performance-based automatic fault diagnosis of industrial gas turbine engines

    A multi-nets ANN model for real-time performance-based automatic fault diagnosis of industrial gas turbine engines by Tahan, M., Muhammad, M., Abdul Karim, Z.A.

    Published 2017
    “…The ability of all the trained networks of the multi-nets model to detect these faulty conditions was investigated. …”
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  14. 14
    Paddy Plant (Oryza Sativa) Disease Detection Based On Improved Convolution Neural Network

    Paddy Plant (Oryza Sativa) Disease Detection Based On Improved Convolution Neural Network by Marceila Suzie, Ambrose

    Published 2023
    “…It helps to pave the way for effective decision-making in overcoming the issues caused by the paddy diseases. 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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  15. 15
    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
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  16. 16
    Features selection for ids in encrypted traffic using genetic algorithm

    Features selection for ids in encrypted traffic using genetic algorithm by Barati, Mehdi, Abdullah, Azizol, Mahmod, Ramlan, Mustapha, Norwati, Udzir, Nur Izura

    Published 2013
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  17. 17
    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
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  18. 18
    Performance comparison between RGB and HSV color segmentations for road signs detection

    Performance comparison between RGB and HSV color segmentations for road signs detection by Mohd Ali, Nursabillilah, Mohd Mustafah, Yasir, Alang Md Rashid, Nahrul Khair

    Published 2013
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  19. 19
    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
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  20. 20
    The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach

    The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach by Ab. Malik, Rosely, Jamil S., Mohamed

    Published 2001
    “…Using the developed algorithm, the safety measures involved are such as reliability index and the probability of failure; instead of only factor of safety if conventional deterministic approach is used. …”
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