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  1. 1
    Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering

    Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

    Published 2024
    “…To address this issue, this study incorporated joint graph learning from the gmc algorithm into swmcan, creating a new algorithm called swmcan-jg. …”
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  2. 2
    The application of suitable sports games for junior high school students based on deep learning and artificial intelligence

    The application of suitable sports games for junior high school students based on deep learning and artificial intelligence by Ji, Xueyan, Samsudin, Shamsulariffin, Hassan, Muhammad Zarif, Farizan, Noor Hamzani, Yuan, Yubin, Chen, Wang

    Published 2025
    “…This study intends to develop a Spatial Temporal-Graph Convolutional Network (ST-GCN) action detection algorithm based on the MediaPipe framework. …”
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  3. 3
    Optimizing kindergarten schedule using : graph coloring / Nur Nabilah Salleh Muner

    Optimizing kindergarten schedule using : graph coloring / Nur Nabilah Salleh Muner by Salleh Muner, Nur Nabilah

    Published 2019
    “…It provides platform for developing early childhood education that combines learning with play. …”
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  4. 4
    An improved directed random walk framework for cancer classification using gene expression data

    An improved directed random walk framework for cancer classification using gene expression data by Seah, Choon Sen

    Published 2020
    “…From the perspective of computing, an algorithm is developed to ease the diagnosis process, but the feasibility is not reliable. …”
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  5. 5
    The conceptual framework of knowledge of large scale and incomplete graphs of skyline queries optimization using machine learning

    The conceptual framework of knowledge of large scale and incomplete graphs of skyline queries optimization using machine learning by Noor, Ubair, Hassan, Raini, Dwi Handayani, Dini Oktarina

    Published 2025
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  6. 6
    Industry 5.0 and Education 5.0: Transforming Vocational Education through Intelligent Technology

    Industry 5.0 and Education 5.0: Transforming Vocational Education through Intelligent Technology by Zhang, Hongli, Leong, Wai Yie

    Published 2024
    “…By analyzing the research gaps in personalized learning paths, emotion-driven learning, crossdisciplinary integration, and long-term learning behavior analysis, the paper proposes four improved algorithms: the adaptive learning path generation algorithm, the emotion-driven personalized learning algorithm, the cross-disciplinary knowledge graph algorithm, and the long-term learning behavior prediction algorithm. …”
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  7. 7
    A Divide-and-Distribute Approach to Single-Cycle Learning HGN Network for Pattern Recognition

    A Divide-and-Distribute Approach to Single-Cycle Learning HGN Network for Pattern Recognition by Muhamad Amin , Anang Hudaya, Khan, Asad I.

    Published 2010
    “…Distributed Hierarchical Graph Neuron (DHGN) is a single-cycle learning distributed pattern recognition algorithm, which reduces the computational complexity of existing pattern recognition algorithms by distributing the recognition process into smaller clusters. …”
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  8. 8
    Graphing calculator exposure of mathematics learning in a partially technology incorporated environment

    Graphing calculator exposure of mathematics learning in a partially technology incorporated environment by Kharuddin, Azrul Fazwan, Ismail, Noor Azina

    Published 2017
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  9. 9
    Bipartite graph approach to course timetabling problems / Hafizah A Razak

    Bipartite graph approach to course timetabling problems / Hafizah A Razak by A Razak, Hafizah

    Published 2009
    “…The prototype is design using constructive heuristic algorithm and colouring the edge of two bipartite graphs. …”
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  10. 10
    Interactive learning package for artificial neural network (Demonstration Module) / Camellia Mohd Kamal

    Interactive learning package for artificial neural network (Demonstration Module) / Camellia Mohd Kamal by Camellia , Mohd Kamal

    Published 2004
    “…Interactive Learning Package for Artificial Neural Network (Demonstration Module) is a learning package that allow the users to learn and enhance the understanding of the ANN subject in more detailed way and apply in the demonstration parts. …”
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  11. 11
    Development of deep reinforcement learning based resource allocation techniques in cloud radio access network

    Development of deep reinforcement learning based resource allocation techniques in cloud radio access network by Amjad, Iqbal

    Published 2022
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  12. 12
    CAGDEEP : Mobile malware analysis using force atlas 2 with strong gravity call graph and deep learning

    CAGDEEP : Mobile malware analysis using force atlas 2 with strong gravity call graph and deep learning by Nur Khairani, Kamarudin, Ahmad Firdaus, Zainal Abidin, Azlee, Zabidi, Mohd Faizal, Ab Razak

    Published 2023
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  13. 13
    Prediction of customer churn for ABC Multistate Bank using machine learning algorithms / Hui Shan Hon ... [et al.]

    Prediction of customer churn for ABC Multistate Bank using machine learning algorithms / Hui Shan Hon ... [et al.] by Hui, Shan Hon, Khai, Wah Khaw, XinYing, Chew, Wai, Peng Wong

    Published 2023
    “…The purpose of this study is to apply machine learning algorithms to develop the most effective model for predicting bank customer churn. …”
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  14. 14
    Examination timetabling for undergraduate programme using graph coloring approach / Norarida Abd Rhani ... [et al.]

    Examination timetabling for undergraduate programme using graph coloring approach / Norarida Abd Rhani ... [et al.] by Abd Rhani, Norarida, Mat Saad, Nor Najihah, Zulkfeli, Nabilah, Mazlan, Mardhiyah Marisha, Mahmud, Maziah, Mohamad, Siti Nurul Fitriah, Wan Yusoff, Wan Roslini

    Published 2021
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  15. 15
    Image Classification for Age-related Macular Degeneration Screening Using Hierarchical Image Decompositions and Graph Mining

    Image Classification for Age-related Macular Degeneration Screening Using Hierarchical Image Decompositions and Graph Mining by Mohd Hanafi Ahmad Hijazi, Chuntao Jiang, Frans Coenen, Yalin Zheng

    Published 2011
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  16. 16
    Visual Crowd Counting System Using Deep Learning

    Visual Crowd Counting System Using Deep Learning by Mohd Wafi Nazrul Adam, Mohd Ridhwan Oxley Adam

    Published 2021
    “…This project is about developing a visual crowd counting system using deep learning. …”
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  17. 17
    Agarwood oil grade clustering of aquilaria malaccensis species using Extraction by GC-MS analysis: Efficient KNN algorithm based on patterns visualization of two-dimensional graph

    Agarwood oil grade clustering of aquilaria malaccensis species using Extraction by GC-MS analysis: Efficient KNN algorithm based on patterns visualization of two-dimensional graph by Siti Mariatul Hazwa, Mohd Huzir, Anis Hazirah ‘Izzati H., Al-Hadi, Amir Hussairi, Zaidi, Nurlaila F., Ismail, Zakiah, Mohd Yusoff, Saiful Nizam, Tajuddin, Mohd Nasir, Taib

    Published 2024
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  18. 18
    Key concept identification: A comprehensive analysis of frequency and topical graph-based approaches

    Key concept identification: A comprehensive analysis of frequency and topical graph-based approaches by Aman, M., Said, A.M., Kadir, S.J.A., Ullah, I.

    Published 2018
    “…The objective of the study presented in this paper is to perform a comprehensive empirical analysis of selected frequency and topical graph-based algorithms for key concept extraction on three different datasets, to identify the major sources of error in these approaches. …”
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  19. 19
    Key concept identification: A comprehensive analysis of frequency and topical graph-based approaches

    Key concept identification: A comprehensive analysis of frequency and topical graph-based approaches by Aman, M., Said, A.M., Kadir, S.J.A., Ullah, I.

    Published 2018
    “…The objective of the study presented in this paper is to perform a comprehensive empirical analysis of selected frequency and topical graph-based algorithms for key concept extraction on three different datasets, to identify the major sources of error in these approaches. …”
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  20. 20
    SUDOKU HELPER

    SUDOKU HELPER by Abdul Razak, Muhammad Asyraf

    Published 2015
    “…In this paper research, author presents an algorithm to provide a tutorial for any Sudoku player who got stuck during the solving process. …”
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