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  1. 1
    Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition

    Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2021
    “…This paper proposed the fuzzy-ID3 (FID3) algorithm, a fuzzy decision tree as the classification method in breast cancer detection. …”
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  2. 2
    Automatic topic-based web page classification using deep learning

    Automatic topic-based web page classification using deep learning by Siti Hawa, Apandi, Jamaludin, Sallim, Rozlina, Mohamed, Norkhairi, Ahmad

    Published 2023
    “…However, there is lack of study that review classification of web pages using deep learning. In this study, the automatic topic-based classification of web pages utilising deep learning that has been proposed by many key researchers are reviewed. …”
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  3. 3
    Automatic Topic-Based Web Page Classification Using Deep Learning

    Automatic Topic-Based Web Page Classification Using Deep Learning by Siti Hawa, Apandi, Jamaludin, Sallim, Rozlina, Mohamed, Norkhairi, Ahmad

    Published 2023
    “…However, there is lack of study that review classification of web pages using deep learning. In this study, the automatic topic-based classification of web pages utilising deep learning that has been proposed by many key researchers are reviewed. …”
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  4. 4
    An Algorithm for Fingerprint Classification Using Template Matching Technique

    An Algorithm for Fingerprint Classification Using Template Matching Technique by Al-Kaissi, Ahmed Wathik Naji

    Published 2002
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  5. 5
    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices

    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2013
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  6. 6
    Performance evaluation of real-time multiprocessor scheduling algorithms

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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  7. 7
    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
    “…This reserarch adapted a methodology of computer vision and algorithms that exploit image segmentation, feature extraction and fuzzy classification to guide the research activities. …”
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  8. 8
    Efficient and low complexity modulation classification algorithm for MIMO systems

    Efficient and low complexity modulation classification algorithm for MIMO systems by Bahloul, M.R., Yusoff, M.Z., Saad, M.N.M.

    Published 2015
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  9. 9
    Waste classification using support vector machine with SIFT-PCA feature extraction

    Waste classification using support vector machine with SIFT-PCA feature extraction by Puspaningrum, Adita Putri, Endah, Sukmawati Nur, Sasongko, Priyo Sidik, Kusumaningrum, Retno, ., Khadijah, ., Rismiyati, Ernawan, Ferda

    Published 2020
    “…This research proposes waste image classification to support automatic waste sorting using Support Vector Machine (SVM) classification algorithm and SIFT-PCA (Scale Invariant Feature Transform - Principal Component Analysis) feature extraction. …”
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  10. 10
    The efficacy of deep learning algorithm in classifying chilli plant growth stages

    The efficacy of deep learning algorithm in classifying chilli plant growth stages by Muammar Rozilan, Danial Mirza, Hanafi, Marsyita, Ali, Roslizah, Razak, Mohd Adib, Cui, Hairu

    Published 2021
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  11. 11
    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images

    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

    Published 2024
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  12. 12
    Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network

    Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network by Sefidgar, Seyed Mohammad Hossein

    Published 2014
    “…This method resulted around 99% of classification rate. To conclude, multi objective parallel genetic algorithm can automatically tune feed forward neural network to classify the dataset with a good classification rate.…”
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  13. 13
    Route Optimization System

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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  14. 14
    Feature-based face recognition system using utilized artificial neural network

    Feature-based face recognition system using utilized artificial neural network by Chai, Tong Yuen

    Published 2010
    “…The main contributions of this project are the automatic algorithms for mouth detection, facial features cropping and face classification. …”
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  15. 15
    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
    “…The feature extraction methods evaluated were Grayscale Pixel Values, Mean Pixel Value of Channels, and Extracting Edge Features. The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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  16. 16
    Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification

    Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification by Sobhan Sheykhivand, Tohid Yousefi Rezaii, Zohreh Mousavi, Azra Delpak, Ali Farzamnia

    Published 2020
    “…In this research, a fully automated system is presented to automatically detect the various states of the epileptic seizure. …”
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  17. 17
    Automatic detection of voice disorders using self loop architecture in back propagation network

    Automatic detection of voice disorders using self loop architecture in back propagation network by Murugesa Pandiyan, Paulraj, Prof. Madya Dr, Sazali, Yaacob, Prof. Dr., Sivanandam, S. N., Muthusamy, Hariharan, Dr.

    Published 2011
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  18. 18
    The Contribution of Feature Selection and Morphological Operation For On-Line Business System’s Image Classification

    The Contribution of Feature Selection and Morphological Operation For On-Line Business System’s Image Classification by Mokhairi, Makhtar, Engku Fadzli Hasan, Syed Abdullah, Fatma Susilawati, Mohamad

    Published 2015
    “…Classification process is part of the important phase in automatic image annotation (AIA). …”
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  19. 19
    Weed recognition based on erosion and dilation segmentation algorithm

    Weed recognition based on erosion and dilation segmentation algorithm by S., Sulaiman, M.H., Siddiqi, I., Ahmad

    Published 2009
    “…Many attempts have been made to develop efficient algorithms for recognition and classification. Currently research is going on for developing new machine vision algorithms for automatic recognition and classification of many divers object groups. …”
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  20. 20
    Advances in automatic insect classification

    Advances in automatic insect classification by Hassan, Siti Noorul Asiah, Abdul Rahman, Nur Nadiah Syakira, Htike@Muhammad Yusof, Zaw Zaw, Shoon , Lei Win

    Published 2014
    “…We provides discussion on the state-of-the-art and provides perspective on future research direction in insect recognition and classification problem.…”
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