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  1. 1
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In addition, the best band selected for image classification is not necessarily the best for classification.A Best Band Selection Index (BBSI) algorithm was developed which is capable of selecting the best band combination for image visualization and supervised classification. …”
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  2. 2
    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
    “…The key metrics for the evaluation are classification accuracy, classification precision and classification recall. 855 images were used to train and test the algorithms. …”
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  3. 3
    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC

    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…The algorithm gives a mean accuracy of 84% out of 125 test images.…”
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  4. 4
    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier

    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
    “…In this project, a classification system is proposed with the one-dimensional local binary pattern algorithm (1D-LBP) with the K-Nearest Neighbour (K-NN) classifier and the system is developed by using a Raspberry Pi 3.There are eight different subjects used to classify in this classification system and each subject consists of seven samples of normalized iris image as input to the system. …”
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  5. 5
    Identification and Grading of Manage Using Image Processing

    Identification and Grading of Manage Using Image Processing by Shukor, Syazwan

    Published 2021
    “…The criteria of mangos to be assessed by the grading algorithm are color and weight. Classification of these mangos are conducted based on standards set by Federal Agriculture Marketing Authority (FAMA) mango ripeness index, Project activities have started using a proposed activity flow for algorithm development using Python and the experimental chamber setup for actual mange data collection. …”
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  6. 6
    Scene illumination classification based on histogram quartering of CIE-Y component

    Scene illumination classification based on histogram quartering of CIE-Y component by Hesamian, Mohammad Hesam

    Published 2014
    “…The result of categorization will be validated using inherent illumination data of scene. Applying the improving algorithm for characterizing histograms (histogram quartering) handed out the advantages of high accuracy. …”
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  7. 7
    Development Of An Algorithm To Reduce The Topographical Effects In Reflected Radiance

    Development Of An Algorithm To Reduce The Topographical Effects In Reflected Radiance by Yeap, Eng Choo

    Published 2020
    “…The algorithm was tested on 11 Landsat 8 OLI satellite images assessed with 120 sample points each. …”
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  8. 8
    A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping

    A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping by Ahmed Asal Kzar, Ahmed Asal Kzar, M Jafri, Mohd Zubir, Mutter, Kussay N., Anwar, Saumi Syahreza

    Published 2016
    “…The first group was used as source samples for supervisor classification via the MHNNA. …”
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  9. 9
    Automatic Classification of Cervix Type

    Automatic Classification of Cervix Type by Muktiar Singh, Jasdeep Singh

    Published 2019
    “…Due to that, in this study, few algorithms were developed by using image classification methods to correctly classify the cervix types based on cervical images by using segmentation and classification method. …”
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  10. 10
    Supervised ANN classification for engineering machined textures based on enhanced features extraction and reduction scheme

    Supervised ANN classification for engineering machined textures based on enhanced features extraction and reduction scheme by Ashour, Mohammed Waleed, Khalid, Fatimah, Al-Obaydee, Mohammed

    Published 2013
    “…Image classification involves the act of classifying images according to their extracted and selected features. …”
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  11. 11
    Machine learning application for concrete surface defects automatic damage classification

    Machine learning application for concrete surface defects automatic damage classification by Syahrul Fithry Senin, Khairullah Yusuf, Amer Yusuf, Rohamezan Rohim

    Published 2024
    “…The Gray Level Co-Occurrence Matrix (GLCM) is used to create an image processing and feature extraction algorithm. …”
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  12. 12
    Mapping sea grass coverage of Tanjung Benoa Bali using medium resolution satellite imagery sentinel 2B

    Mapping sea grass coverage of Tanjung Benoa Bali using medium resolution satellite imagery sentinel 2B by Hidayah, Zainul, Vieira, Lucas De Oliveira, Safitri, Rahma, Rachman, Herlambang Aulia, As-Syakur, Abdur Rahman

    Published 2023
    “…The objectives of this study were, firstly to identify the distribution of seagrass beds in Tanjung Benoa using Sentinel 2B satellite imagery and secondly to compare classification results from two different approaches namely pixel-based image classification and object-based image classification. …”
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  13. 13
    Mixed waste classification based on vision inspection / Hassan Mehmood Khan

    Mixed waste classification based on vision inspection / Hassan Mehmood Khan by Hassan Mehmood , Khan

    Published 2022
    “…A total of 640 samples of image data was collected, out of which 320 image data was used for training of machine learning model while the remaining 320 image data was used for testing purposes. …”
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  14. 14
    EEG Spectrogram Classification Employing ANN for IQ Application

    EEG Spectrogram Classification Employing ANN for IQ Application by Mahfuzah, Mustafa, Mohd Nasir, Taib, Sahrim, Lias, Zunairah, Murat, Norizam, Sulaiman

    Published 2013
    “…Then, Principal Component Analysis (PCA) is used to reduce the big matrix, and is followed with the classification of the EEG spectrogram image in IQ application using ANN algorithm. …”
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  15. 15
    Development Of Algorithms For Vehicle Classification And Speed Estimation From Dynamic Scenes By On-Board Camera Using Image Processing Techniques

    Development Of Algorithms For Vehicle Classification And Speed Estimation From Dynamic Scenes By On-Board Camera Using Image Processing Techniques by Aminuddin, Nur Shazwani

    Published 2018
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  16. 16
    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
    “…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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  17. 17
    Classification of EEG Spectrogram Using ANN for IQ Application

    Classification of EEG Spectrogram Using ANN for IQ Application by Mahfuzah, Mustafa, Norizam, Sulaiman

    Published 2013
    “…Then, ANN algorithm is employed to classify the EEG spectrogram image in IQ application. …”
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  18. 18
    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
    “…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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  19. 19
    Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud

    Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud by Mahmud, Nur Farahana

    Published 2022
    “…Nowadays, there are numerous license plate recognition systems that have been developed and analysed effectively by previous researchers using different machine learning algorithms. However, according to a recent study, ANN algorithms require a huge amount of training data while BPFFNN algorithms only have an average success rate of 70% in recognizing all the characters. …”
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  20. 20
    Online sequential extreme learning machine for classification of Mycobacterium tuberculosis in Ziehl-Neelsen stained tissue

    Online sequential extreme learning machine for classification of Mycobacterium tuberculosis in Ziehl-Neelsen stained tissue by Muhammad Khusairi, Osman, Mohd Yusoff, Mashor, Prof. Dr., Hasnan, Jaafar, Assoc. Prof. Dr.

    Published 2012
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