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  1. 1

    An Ar Natural Marker Similarities Measurement Algorithm For E-Biodiversity by Tan, Mei Synn, Wang, Yin Chai

    Published 2018
    “…The objective of this research is to comparatively evaluate the effectiveness of different algorithms, method combination procedure, and their parameters towards classification accuracy. …”
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    Proceeding
  2. 2

    Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

    Published 2021
    “…Optimization algorithms are widely used for the identification of intrusion. …”
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    Article
  3. 3

    Data mining in mobile ECG based biometric identification by Sidek, Khairul Azami, Mai, Vu, Khalil, Ibrahim

    Published 2014
    “…Experimentation results showed that our method simplifies biometric identification process by obtaining reduced computational complexity when compared to other related algorithms. …”
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    Article
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    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

    Published 2020
    “…This study proposed an integrated system for EEG signals pre-processing by using machine learning algorithms in the identification of artifactual components during the process of Wavelet-ICA. …”
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    Thesis
  7. 7

    Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs by Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Mohd Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl

    Published 2021
    “…Therefore, the proposed methods were effective in improving the process of automatic gender recognition from the emotional-based EEG signals.…”
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    Article
  8. 8

    Plant leaf recognition algorithm using ant colony-based feature extraction technique by Ghasab, Mohammad Ali Jan

    Published 2013
    “…Therefore, it can be concluded that the proposed method is capable of a high rate of classification of various plant species.…”
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    Thesis
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  10. 10

    Geometric Feature Extraction for Identification and Classification of Overlapping Cells for Leukaemia by Siew Ming, Kiu, Yin Chai, Wang

    Published 2022
    “…This paper describes the study of overlapping leukaemia cells based on geometric features for identification and classification. …”
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    Article
  11. 11

    Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

    Published 2017
    “…At first, a peak classification algorithm is developed based on the general following processes including peak candidate identification, feature extraction, and classification. …”
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    Thesis
  12. 12

    Region-based segmentation and classification of Mandibular First Molar Tooth based on Demirjian’s method by Norhasmira, Mohammad, M Y P M, Yusof, Rohana, Ahmad, Anuar Mikdad, Muad

    Published 2020
    “…A region-based segmentation method known as Watershed Transform associated with several image enhancement algorithms is implemented. …”
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    Article
  13. 13

    Fingerprint feature extraction based discrete cosine transformation (DCT) by Chin Kim On, Paulraj M. Pandiyan, Sazali Yaacob, Azali Saudi

    Published 2009
    “…The proposed algorithm involved two stages, which is pre-processing of fingerprint image and feature extraction based nCT. …”
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    Proceedings
  14. 14

    Geometric Feature Extraction for Identification and Classification of the Overlapping Cells for Leukaemia by Kiu, Siew Ming

    Published 2018
    “…Tests of cell counting in between the two stages, which are before and after for the process of identification and classification of overlapping cells. …”
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    Thesis
  15. 15

    Wood texture detection with conjugate gradient neural network algorithm by Widyarto, Setyawan, Suryasa, I. Nyoman, Khairul Annuar, Abdullah, Fajarianto, Otto, Mohd Shafry, Mohd Rahim, Priyandoko, Gigih, Budaya, Gilang Anggit

    Published 2017
    “…The experiments are based on artificial neural network (ANN) algorithm that used back propagation and conjugate gradient method of training function in the process of identification. …”
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    Conference or Workshop Item
  16. 16

    Dense-cluster based voting approach for license plate identification by Asadzadehkaljahi, Maryam, Shivakumara, Palaiahnakote, Roy, Sangheeta, Olatunde, Mojeed Salmon, Anisi, Mohammad Hossein, Lu, Tong, Pal, Umapada

    Published 2018
    “…Finally, we propose voting for the responses of hypotheses for identification. Classification results with existing methods show that the proposed method outperforms existing methods since the it works based on the distribution of foreground and background pixels rather than character shapes. …”
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    Article
  17. 17

    Review of Wheat Disease Classification and Severity Detection Models by Hongyan, Zang, Annie, Joseph, Shourong, Zhang, Rong, Liu, Wanzhen, Wang

    Published 2023
    “…This paper mainly aims to explain deep learning-based wheat diseases identification algorithm, and to discuss the benefits and drawbacks of present wheat disease detection approaches. …”
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    Article
  18. 18

    Speaker identification through feature fusion based deep learning / Rashid Jahangir by Rashid , Jahangir

    Published 2021
    “…Finally, this study also investigated the effectiveness of one-level (identifying speaker) and two-level (identify the gender first and then identify the speaker) classification methods for speaker identification. The experimental results showed that two-level classification presented better results compared to one-level classification. …”
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    Thesis
  19. 19

    Multilocal feature selection using genetic algorithm for face identification by Mohamad, Dzulkifli

    Published 2008
    “…This paper presents an improved offline face recognition algorithm based on a multi-local feature selection approach for grayscale images. …”
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    Article
  20. 20

    Comparison of fully automated and semi-automated methods for species identification by Kalafi, Elham Yousef, Anuar, M.K., Sakharkar, Meena Kishore, Dhillon, Sarinder Kaur

    Published 2018
    “…In order to assist taxonomists, many methods and algorithms have been proposed to develop semi-automated and fully automated systems for species identification. …”
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    Article