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  1. 1
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  2. 2
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  3. 3
    Machine learning model for performance prediction in mobile network management / Muhammad Hazim Wahid

    Machine learning model for performance prediction in mobile network management / Muhammad Hazim Wahid by Wahid, Muhammad Hazim

    Published 2022
    “…One of the major challenges when applying machine learning is to identify the best algorithm from a variety of algorithms to solve a problem. …”
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  4. 4
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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  5. 5
    Federated deep learning for automated detection of diabetic retinopathy

    Federated deep learning for automated detection of diabetic retinopathy by Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani

    Published 2022
    “…Federated learning allows deep learning algorithms to learn from a diverse set of data stored in multiple databases. …”
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  6. 6
    Design and optimization of a test case generation algorithm for real-time embedded systems based on adaptive Q-Learning

    Design and optimization of a test case generation algorithm for real-time embedded systems based on adaptive Q-Learning by Yingbei, Niu, Chai, Soo See

    Published 2026
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  7. 7
    Super resolution imaging using modified lanr based on separable filtering

    Super resolution imaging using modified lanr based on separable filtering by Somadina, Ike Chidiebere

    Published 2019
    “…Reaching super resolution has been a challenge in image processing practices, because of their under-constrained nature that requires the missing HR image details to be reconstructed. …”
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  8. 8
    Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase

    Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase by Che Mat @ Mohd Shukor, Zamzarina, Md Sap, Mohd Noor

    Published 2004
    “…We proposed KMeans clustering algorithm that is based on multidimensional scaling, joined with neural knowledge based technique algorithm for supporting the learning module to generate interesting clusters that will generate interesting rules for extracting knowledge from stock exchange databases efficiently and accurately.…”
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  9. 9
    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches

    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

    Published 2018
    “…Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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  10. 10
    Benchmarking Robust Machine Learning Models Under Data Imperfections in Real-World Data Science Scenarios

    Benchmarking Robust Machine Learning Models Under Data Imperfections in Real-World Data Science Scenarios by Marlindawati, ., Mohammad, Azhar, Esha, Sabir

    Published 2026
    “…Multiple classical machine learning algorithms and deep learning models were assessed across diverse benchmark datasets. …”
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  11. 11
    Sentiment analysis of customer review for Tina Arena Beauty

    Sentiment analysis of customer review for Tina Arena Beauty by Amri, Nur Najwa Shahirah

    Published 2025
    “…Customer review data were collected from multiple platforms and processed using Natural Language Processing (NLP) techniques such as Term Frequency-Inverse Document Frequency (TF-IDF). Three machine learning algorithms Naive Bayes, Random Forest, and Support Vector Machine (SVM) were evaluated, and SVM achieved the highest accuracy and was selected as the final classifier. …”
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  12. 12
    Product design and development strategies for an automated Printed Circuit Board (PCB) defects detection systems

    Product design and development strategies for an automated Printed Circuit Board (PCB) defects detection systems by Kamaruddin, Shafie, Shamsulamri, Saiffaqrullah, Sharwazi, Muhammad Haziq Fakhri, Suhaimi, Muhammad Harith Ikhmal, Mohamad, Muhamad Ariff Othmani, Sukindar, Nor Aiman, Ahmad Azhar, Ahmad Zahirani

    Published 2024
    “…This approach provides a practical and economical solution for PCB defect detection, merging advanced object detection algorithms with accessible, cost-effective hardware. …”
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  13. 13
    Cloud-based lightweight detection of hardhat compliance based on YOLOv5 in power construction site

    Cloud-based lightweight detection of hardhat compliance based on YOLOv5 in power construction site by Wanbo, Luo

    Published 2025
    “…Therefore, this thesis explores and studies public hardhat datasets, deep learning algorithms, power Internet of Things (PIoT), and edge computing to address the above issues. …”
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  14. 14
    An automated Printed Circuit Board (PCB) defects detection system

    An automated Printed Circuit Board (PCB) defects detection system by Kamaruddin, Shafie, Shamsulamri, Saiffaqrullah, Sharwazi, Muhammad Haziq Fakhri, Suhaimi, Muhammad Harith Ikhmal, Mohamad, Muhamad Ariff Othmani, Sukindar, Nor Aiman, Ahmad Azhar, Ahmad Zahirani

    Published 2025
    “…By combining advanced object detection algorithms with affordable hardware, this method offers a practical and cost-effective solution for PCB defect detection. …”
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