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  1. 1
    Optimized image enhancement of colour processing for retinal fundus image

    Optimized image enhancement of colour processing for retinal fundus image by Nurul Atikah, Mohd Sharif

    Published 2025
    “…It achieved a 95.034% success rate in classification accuracy. The study introduces a new colour correction model and an optimized image enhancement model, significantly improving retinal fundus image quality and establishing the most effective model for image quality enhancement…”
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  2. 2
    Optimized image enhancement of colour processing for retinal fundus image

    Optimized image enhancement of colour processing for retinal fundus image by Nurul Atikah, Mohd Sharif

    Published 2025
    “…It achieved a 95.034% success rate in classification accuracy. The study introduces a new colour correction model and an optimized image enhancement model, significantly improving retinal fundus image quality and establishing the most effective model for image quality enhancement…”
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  3. 3
    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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  4. 4
    Feature fusion using a modified genetic algorithm for face and signature recognition system

    Feature fusion using a modified genetic algorithm for face and signature recognition system by Suryanti, Awang

    Published 2015
    “…Most existing systems are dealing with feature fusion of the same domain such as image based of fingerprint and face. Thus, there is no issue of incompatible features to be fused compared to the proposed development. …”
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  5. 5
    Satellite Image Segmentation Using Thresholding Technique

    Satellite Image Segmentation Using Thresholding Technique by Khalik, Mohd Haffez

    Published 2017
    “…It is a key step for image analysis, comprehension and description. Among all the segmentation techniques, thresholding segmentation method is the most popular algorithm and is widely used in the image segmentation field. …”
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  6. 6
    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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  7. 7
    Enhancing land cover classification in remote sensing imagery using an optimal deep learning model

    Enhancing land cover classification in remote sensing imagery using an optimal deep learning model by Motwake, Abdelwahed, Hassan Abdalla Hashim, Aisha, Obayya, Marwa, Eltahir, Majdy M.

    Published 2023
    “…The current study presents an Improved Sand Cat Swarm Optimization with Deep Learning-based Land Cover Classification (ISCSODL-LCC) approach on the RSIs. …”
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  8. 8
    Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza

    Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza by Khaimuza, Haris Hidayatullah

    Published 2024
    “…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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  9. 9
    Formulation of invariants for discrete orthogonal moments and image classification / Pee Chih Yang

    Formulation of invariants for discrete orthogonal moments and image classification / Pee Chih Yang by Pee, Chih Yang

    Published 2013
    “…Therefore new sets of invariant algorithms have been proposed to resolve the above mentioned issues. …”
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  10. 10
    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms

    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

    Published 2024
    “…It involves identifying and isolating relevant information from the images that classification algorithms can use to distinguish between different fruit categories. …”
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  11. 11
    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…In general, image segmentation isolates an object from the images, feature extraction creates features for classification phase while object classification categorizes objects into the correct groups. …”
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  12. 12
    Automatic multilevel medical image annotation and retrieval

    Automatic multilevel medical image annotation and retrieval by Mueen, A., Zainuddin, R., Baba, M.S.

    Published 2008
    “…Image annotation performance largely depends on three issues: (1) automatic image feature extraction; (2) a semantic image concept modeling; (3) algorithm for semantic image annotation. …”
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  13. 13
    Image classification of Aedes mosquitoes using transfer learning / Zetty Ilham Abdullah

    Image classification of Aedes mosquitoes using transfer learning / Zetty Ilham Abdullah by Abdullah, Zetty Ilham

    Published 2021
    “…In recent years, the importance, and uses of computer vision, notably image classification, to tackle real-world issues have grown. …”
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  14. 14
    Phishing image spam classification research trends: Survey and open issues

    Phishing image spam classification research trends: Survey and open issues by John Abari, Ovye, Mohd Sani, Nor Fazlida, Khalid, Fatimah, Mohd Yunus Bin Sharum, Mohd Yunus, Mohd Ariffin, Noor Afiza

    Published 2020
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  15. 15
    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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  16. 16
    Transfer Learning for Lung Nodules Classification with CNN and Random Forest

    Transfer Learning for Lung Nodules Classification with CNN and Random Forest by Abdulrazak, Saleh, Chee, Ka Chin, Ros Ameera, Rosdi

    Published 2023
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  17. 17
    Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques

    Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques by Arif Z.H., Mahmoud M.A., Abdulkareem K.H., Mohammed M.A., Al-Mhiqani M.N., Mutlag A.A., Dama�evi?ius R.

    Published 2023
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  18. 18
    Transfer Learning for Lung Nodules Classification with CNN and Random Forest

    Transfer Learning for Lung Nodules Classification with CNN and Random Forest by Abdulrazak Yahya, Saleh, Chee, Ka Chin, Ros Ameera, Rosdi

    Published 2024
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  19. 19
    An improved method using fuzzy system based on hybrid boahs for phishing attack detection

    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
    “…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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  20. 20
    Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm

    Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm by Ismail, Asmida, Ahmad, Siti Anom, Che Soh, Azura, Hassan, Mohd Khair, Harith, Hazreen Haizi

    Published 2020
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