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  1. 1
    An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images

    An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images by Ibrahim, I., Ibrahim, Z., Khalil, K., Mokji, M.M., Abu Bakar, S.A.R.S., Mokhtar, N., Ahmad, W.K.W.

    Published 2012
    “…The improved PCB defect classification algorithm has been applied to real PCB images to successfully classify all of the defects. …”
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  2. 2
    Software defect prediction framework based on hybrid metaheuristic optimization methods

    Software defect prediction framework based on hybrid metaheuristic optimization methods by Wahono, Romi Satria

    Published 2015
    “…The classification algorithm is a popular machine learning approach for software defect prediction. …”
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  3. 3
    Using the bees algorithm to optimise a support vector machine for wood defect classification

    Using the bees algorithm to optimise a support vector machine for wood defect classification by Pham, D.T, Muhammad, Zaidi, Mahmuddin, Massudi, Ghanbarzadeh, Afshin, Koc, Ebubekir, Otri, Sameh

    Published 2007
    “…This paper describes a new application of the Bees Algorithm to the optimization of a Support Vector Machine (SVM) for the problem of classifying defects in plywood. …”
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  4. 4
    An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images

    An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images by Ismail, Ibrahim, Zuwairie, Ibrahim, Kamal, Khalil, Musa, Mohd Mokji, Syed Abdul Rahman, Syed Abu Bakar, Norrima, Mokhtar, Wan Khairunizam, Wan Ahmad

    Published 2012
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  5. 5
    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection

    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

    Published 2015
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  6. 6
    Evolutionary Fuzzy ARTMAP Neural Networks for Classification of Semiconductor Defects

    Evolutionary Fuzzy ARTMAP Neural Networks for Classification of Semiconductor Defects by Zuwairie, Ibrahim, Tan, Shing Chiang, Watada, Junzo, Marzuki, Khalid

    Published 2014
    “…The outcomes positively indicate the effectiveness of the proposed networks in handling classification problems with imbalanced data sets.…”
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  7. 7
    Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules

    Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules by Wiliani, Ninuk

    Published 2023
    “…However, high similarity of characteristics among the shapes and textures has been a major challenge in defect classification process. The objective of this research was to develop and analyse feature extraction used for classification techniques for defect detection of solar photovoltaic modules surfaces. …”
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  8. 8
    Detection of tube defect using the autoregressive algorithm

    Detection of tube defect using the autoregressive algorithm by Abd Halim, Zakiah, Jamaludin, Nordin, Junaidi, Syarif, Syed Yusainee, Syed Yahya

    Published 2015
    “…Easy detection and evaluation of defect in the tube structure is a continuous problem and remains a significant demand in tube inspection technologies. …”
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  9. 9
    Internal defect detection and reconstruction framework for laminated glass fibre reinforced polymer composite materials

    Internal defect detection and reconstruction framework for laminated glass fibre reinforced polymer composite materials by Ng, Sok Choo

    Published 2013
    “…Therefore, by removmg the low frequency signals, the intemal defect detectability can be improved. Moreover, the classification of an input pattem based on the closest neighbours of the point of interest provides more accurate defect detection in comparison with the classification based on experience data as the defect pattems vary on circumstances in ultrasonic NDE problems.…”
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  10. 10
    Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation

    Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation by Mahdavipour, Zeinab

    Published 2016
    “…The classification combines the analysis of defect intensity features, the application of unsupervised k-mean clustering and multi-class SVM algorithms. …”
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  11. 11
    A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification

    A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification by Suihai, Chen, Chih How, Bong, Po Chan, Chiu

    Published 2024
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  12. 12
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…The K-means algorithm has been around for over a century. …”
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  13. 13
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  14. 14
    Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application

    Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

    Published 2020
    “…This study aims to compare the performance of Boyer-Moore, Knuth morris pratt, and Horspool algorithms in searching for the meaning of words in the Java-Indonesian dictionary search application in terms of accuracy and processing time. …”
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  15. 15
    A three dimensional (3D) vision based defect inspection system for gluing application

    A three dimensional (3D) vision based defect inspection system for gluing application by Harun, Mohamad Haniff

    Published 2013
    “…Each defect has special characteristic. Inspection system developed to identify problems occurs in gluing process. …”
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  16. 16
    Aerial imagery paddy seedlings inspection using deep learning

    Aerial imagery paddy seedlings inspection using deep learning by Anuar, Mohamed Marzhar, Abdul Halin, Alfian, Perumal, Thinagaran, Kalantar, Bahareh

    Published 2022
    “…Deep learning algorithms in computer vision for image classification and object detection can facilitate the agriculture industry, especially in paddy cultivation, to alleviate human efforts in laborious, burdensome, and repetitive tasks. …”
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  17. 17
    Prognostic Health Management of Pumps Using Artificial Intelligence in the Oil and Gas Sector: A Review

    Prognostic Health Management of Pumps Using Artificial Intelligence in the Oil and Gas Sector: A Review by Aliyu, R., Mokhtar, A.A., Hussin, H.

    Published 2022
    “…To further understand its potential, various algorithms and related theories are examined. Based on the examined studies, machine learning shows potential for prognostics and defect diagnosis. …”
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  18. 18
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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  19. 19
    Biometrics electronic purse

    Biometrics electronic purse by Abdul Rahman, Abdul Wahab, Eng, Chong Tan, S., M. Heng

    Published 1999
    “…This paper looked into using biometrics as a mean of authentication, thus requiring a new generation of Smart Card technology to be implemented in banking and multiple applications environment. …”
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  20. 20
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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