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  1. 1

    Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

    Published 2024
    “…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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    Thesis
  2. 2

    An adaptive HMM based approach for improving e-Learning methods by Deeb B., Hassan Z., Beseiso M.

    Published 2023
    “…This adaptive algorithm can thus be applied to any e-learning platform for optimal content delivery to its users in real-time. © 2014 IEEE.…”
    Conference Paper
  3. 3

    Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

    Published 2022
    “…In particular, this study proposes a crime prediction and evaluation framework for machine learning algorithms of the network edge. …”
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    Conference or Workshop Item
  4. 4

    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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    Thesis
  5. 5

    Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm by Abd Rahman, Mohd Shahrizan, Jamaludin, Nor Azliana Akmal, Zainol, Zuraini, Tengku Sembok, Tengku Mohd

    Published 2025
    “…The central purpose of this research is to significantly increase the predictability of these milestone dates, thereby eliminating the risks associated with high and dynamic fluctuations in schedules. The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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    Article
  6. 6

    Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

    Published 2021
    “…In essence, the method is to use a reward-based learning environment to watch how the agent makes decisions. …”
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    Monograph
  7. 7

    Defects identification on semiconductor wafer for yield improvement using machine learning / Pedram Tabatabaeemoshiri by Pedram , Tabatabaeemoshiri

    Published 2025
    “…This study addresses the urgent issue of detecting hidden defects in semiconductor wafers that conventional methods overlook. This work presents a novel graph-based semi-supervised learning (GSSL) algorithm designed for wafer defect detection. …”
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    Thesis
  8. 8
  9. 9

    A Stepper Motor Design Optimization Using by Wong, Chin Wei

    Published 2005
    “…In order to achieve the optimum design, Genetic Algorithms (GAs) approach has been applied. GAs approach is selected because it is a powerful and broadly applicable stochastic search and optimization techniques that works for many problems that are very difficult to solve by conventional methods. …”
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    Monograph
  10. 10

    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

    Published 2020
    “…Supervised and unsupervised machine learning algorithms particularly the Support Vector Machine (SVM) and Density Based Spatial Clustering of Application with Noise (DBSCAN) are used in this study. …”
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    Thesis
  11. 11

    Customer mobile behavioral segmentation and analysis in telecom using machine learning by Sharaf Addin, Eman Hussein, Admodisastro, Novia Indriaty, Mohd Ashri, Siti Nur Syahirah, Kamaruddin, Azrina, Chew, Yew Chong

    Published 2021
    “…This study aims to identify telecom customer segments by utilizing machine learning and subsequently develop a web-based dashboard. …”
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    Article
  12. 12

    Hierarchical extreme learning machine based reinforcement learning for goal localization by AlDahoul, Nouar, Htike, Zaw Zaw, Akmeliawati, Rini

    Published 2017
    “…This paper proposes a combination of Hierarchical Extreme learning machine and Reinforcement learning to find an optimal policy directly from visual input. …”
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    Proceeding Paper
  13. 13

    Lighting enhancement of underwater image using coronavirus herd immunity optimizer by Alyasseri Z.A.A., Ghalib R., Jamil N., Mohammed H.J., Ali N., Ali N.S., Al-Wesabi F.N., Assiri M.

    Published 2025
    “…To this end, this paper proposes a new enhancement method to improve underwater image quality. …”
    Article
  14. 14

    Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning by Lim, Wai Ping, Goh, Ching Pang

    Published 2023
    “…Focusing on clustering algorithms, the study employs popular methods like K-Means Clustering, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Agglomerative Hierarchical Clustering, and Mean Shift Clustering to understand customer characteristics and behaviors. …”
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    Article
  15. 15

    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

    Published 2019
    “…An ensemble of these algorithms is an intelligent and adaptive solution, producing a clean output, while preserving significant pixel information. …”
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    Thesis
  16. 16

    HELM based Reinforcement Learning for Goal Localization by AlDahoul, Nouar, Htike@Muhammad Yusof, Zaw Zaw

    Published 2016
    “…In this paper, reinforcement learning method was utilized to find optimal series of actions to localize the goal region. …”
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    Proceeding Paper
  17. 17

    STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, SAMIR, EL-NAKLA, SADIQ A., ALHUWAIDI

    Published 2021
    “…A profound algorithm comprising of preprocessing in CIELAB color space and Delaunay triangulation based clustering along with Particle Swarm Optimization (PSO) is proposed for the segmentation. …”
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    Article
  18. 18

    Detection of Workers’ Behaviour in the Manufacturing Plant using Deep Learning by Goh, Ching Pang

    Published 2023
    “…Utilizing machine learning algorithms, our system learns and detects intricate activities from worker behavior sequences, offering a sophisticated analysis of worker efficiency. …”
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    Article
  19. 19

    Enhancing minority sentiment classification in gastronomy tourism: a hybrid sentiment analysis framework with data augmentation, feature engineering and business intelligence by Razali, Mohd Norhisham, Hanapi, Rozita, Chiat, Lee Wen, Manaf, Syaifulnizam Abdul, Salji, Mohd Rafiz, Nisar, Kashif

    Published 2024
    “…To address these challenges, our research introduces a hybrid approach, combining various lexicon-based sentiment and emotional analysis algorithms, thereby enhancing the reliability of customer review analysis in the gastronomy tourism sector. …”
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    Article
  20. 20

    Enhancing minority sentiment classification in gastronomy tourism: a hybrid sentiment analysis framework with data augmentation, feature engineering and business intelligence by Razali, Mohd Norhisham, Hanapi, Rozita, Chiat, Lee Wen, Abdul Manaf, Syaifulnizam, Salji, Mohd Rafiz, Nisar, Kashif

    Published 2024
    “…To address these challenges, our research introduces a hybrid approach, combining various lexicon-based sentiment and emotional analysis algorithms, thereby enhancing the reliability of customer review analysis in the gastronomy tourism sector. …”
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    Article