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  1. 1
    The formulation of a transfer learning pipeline for the classification of the wafer defects

    The formulation of a transfer learning pipeline for the classification of the wafer defects by Lim, Shi Xuen

    Published 2023
    “…This often causes misjudgment and inconsistency result between different personnel. Automated processes have been used commonly in recent years, with the judgement done by using conventional image processing algorithm. …”
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  2. 2
    An efficient AdaBoost algorithm for enhancing skin cancer detection and classification

    An efficient AdaBoost algorithm for enhancing skin cancer detection and classification by Gamil, Seham, Zeng, Feng, Alrifaey, Moath, Asim, Muhammad, Ahmad, Naveed

    Published 2024
    “…To improve accuracy, the AdaBoost algorithm is utilized, which amalgamates weak classification models into a robust classifier with high accuracy. …”
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  3. 3
    Residual Attention Network for Brain Tumour Classification

    Residual Attention Network for Brain Tumour Classification by Sashwini, A/P S. Thiagaraju

    Published 2019
    “…The normal CNN algorithm did not perform well with the accuracy being very inconsistent between 57% and 71 %. …”
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  4. 4
    Detection of corneal arcus using rubber sheet and machine learning methods

    Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

    Published 2019
    “…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
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  5. 5
    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
    “…Whilst it was observed that the optimized k-NN model based on the aforesaid pipeline could achieve a classification accuracy of 100% for the training, validation, and tes t data. …”
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  6. 6
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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  7. 7
    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia

    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia by San, Limhwee

    Published 2006
    “…Average filtering was applied to the PM10 map to mininise the noise effect. The proposed algorithms were also validated using the multidate data. …”
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  8. 8
    TB-FusionNet: a multi-scale feature fusion algorithm with spatial and channel cross-attention for tuberculosis detection

    TB-FusionNet: a multi-scale feature fusion algorithm with spatial and channel cross-attention for tuberculosis detection by Ding, Zeyu, Yaakob, Razali, Tieng Wei, Koh, Azman, Azreen, Mohd Rum, Siti Nurulain, Zakaria, Nor Fadhlina, Ahmad Nazri, Azree Shahril

    Published 2026
    “…To address the aforementioned issues, this study proposes TB-FusionNet, a multi-scale feature fusion algorithm based on channel and spatial cross-attention mechanisms, for tuberculosis classification. …”
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  9. 9
    Optimized techniques for landslide detection and characteristics using LiDAR data

    Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

    Published 2018
    “…These results indicated that the proposed models with optimized hyper-parameters produced the accurate classification results. …”
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  10. 10
    Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network

    Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network by Al-Hiyali, M.I., Yahya, N., Faye, I., Hussein, A.F.

    Published 2021
    “…The dynamic FC patterns of wavelet coherence scalogram represent phase synchronization between the pairs of BOLD signals. Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. …”
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  11. 11
    Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network

    Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network by Al-Hiyali, M.I., Yahya, N., Faye, I., Hussein, A.F.

    Published 2021
    “…The dynamic FC patterns of wavelet coherence scalogram represent phase synchronization between the pairs of BOLD signals. Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. …”
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  12. 12
    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods

    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Audrey Huong, Kim Gaik Tay, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

    Published 2023
    “…The HHM combined histogram equalization and morphological and thresholding-based algorithms to localize veins from hand images. The data were divided into training, validation, and testing sets with an 8:1:1 ratio before training AlexNet. …”
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  13. 13
    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods

    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Audrey Huong, Kim Gaik Tay, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

    Published 2023
    “…The HHM combined histogram equalization and morphological and thresholding-based algorithms to localize veins from hand images. The data were divided into training, validation, and testing sets with an 8:1:1 ratio before training AlexNet. …”
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  14. 14
    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods

    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Kim Gaik Tay, Audrey Huong, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

    Published 2023
    “…The HHM combined histogram equalization and morphological and thresholding-based algorithms to localize veins from hand images. The data were divided into training, validation, and testing sets with an 8:1:1 ratio before training AlexNet. …”
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  15. 15
    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods

    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Audrey Huong, Kim Gaik Tay, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

    Published 2023
    “…The HHM combined histogram equalization and morphological and thresholding-based algorithms to localize veins from hand images. The data were divided into training, validation, and testing sets with an 8:1:1 ratio before training AlexNet. …”
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  16. 16
    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods

    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Kim Gaik Tay, Audrey Huong, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

    Published 2023
    “…The HHM combined histogram equalization and morphological and thresholding-based algorithms to localize veins from hand images. The data were divided into training, validation, and testing sets with an 8:1:1 ratio before training AlexNet. …”
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  17. 17
    Relationship between deforestation and land surface temperature across an elevation gradient using satellite imagery in Cameron Highlands, Malaysia

    Relationship between deforestation and land surface temperature across an elevation gradient using satellite imagery in Cameron Highlands, Malaysia by How, Darren Jin Aik

    Published 2021
    “…First, land cover classes and detection were identified using an Object-based Image Analysis (OBIA) classification technique on both Landsat 7 and 8 sensors, using a combination of nearest neighbour and multiresolution segmentation algorithm (MSA). …”
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  18. 18
    Local threshold identification and gray level classification of butt joint welding imperfections using robot vision system

    Local threshold identification and gray level classification of butt joint welding imperfections using robot vision system by Mohd Shah, Hairol Nizam

    Published 2018
    “…The proposed approaches were validated through experiments with a KUKA welding robot in a realistic workshop environment. …”
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  19. 19
    Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification

    Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

    Published 2023
    “…Therefore, an improved feature extraction and selection for sky image classification (FESSIC) algorithm is proposed. …”
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  20. 20
    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani

    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

    Published 2015
    “…The urban growth images obtained are analysed to improve existing classification algorithms. …”
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