Search Results - (( pattern classification methods algorithm ) OR ( pattern classification modified algorithm ))

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  1. 1

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Recently, various techniques based on different algorithms have been developed. However, the classification accuracy and computational cost are not satisfied. …”
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    Thesis
  2. 2

    Modern fuzzy min max neural networks for pattern classification by Al Sayaydeh, Osama Nayel Ahmad

    Published 2019
    “…Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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    Thesis
  3. 3

    Finger Vein Recognition Using Pattern Map As Feature Extraction by Teoh, Saw Beng

    Published 2012
    “…In this thesis, a modified pattern map feature extraction method is proposed for finger vein recognition. …”
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    Thesis
  4. 4

    Study Of EMG Feature Selection For Hand Motions Classification by Abdullah, Abdul Rahim, Mohd Saad, Norhashimah, Too, Jing Wei

    Published 2019
    “…Thus, this paper employs two recent feature selection methods namely competitive binary gray wolf optimizer (CBGWO) and modified binary tree growth algorithm (MBTGA) to evaluate the most informative EMG feature subset for efficient classification. …”
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    Article
  5. 5

    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control by Mohd Hanafi, Muhammad Sidik

    Published 2020
    “…Addition of hybrid automata algorithm to run pattern and non-pattern recognition based control methods is an advantage to increase accuracy in differentiating forward stroke or hand return activity. …”
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    Thesis
  6. 6

    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

    Published 2016
    “…The components of the AIRS2 algorithm that pose problems will be modified. This thesis proposes three new hybrid algorithms: The FRA-AIRS2 algorithm uses fuzzy logic to improve data reduction capability of AIRS2 and to solve the linearity problem associated with resource allocation of AIRS. …”
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    Thesis
  7. 7

    Identifying diseases and diagnosis using machine learning by Iswanto I., Laxmi Lydia E., Shankar K., Nguyen P.T., Hashim W., Maseleno A.

    Published 2023
    “…For classify the disease classification algorithms are used. It uses are many dimensionality reduction algorithms and classification algorithms. …”
    Article
  8. 8

    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
    “…In this study, an algorithm is developed using Multivariate pattern analysis (MVPA) and modified CNN to decode the behavior of brain for different images with limited data set. …”
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    Article
  9. 9

    A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

    Published 2012
    “…The performance of MANFIE was compared with existing methods in a diversity of practical benchmark applications such as pattern classifications, time series predictions, modeling with inverse learning control and mobile robot navigation. …”
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    Thesis
  10. 10

    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…The second method is called the Modified Binary Tree Growth Algorithm (MBTGA) that applies swap, crossover, and mutation operators. …”
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    Thesis
  11. 11

    Pattern generation through feature values modification and decision tree ensemble construction by Akhand, M. A. H, Rahman, M.M. Hafizur, Murase, K.

    Published 2013
    “…The method modifies feature values of some patterns with the values of other patterns to generate different patterns for different classifiers. …”
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    Article
  12. 12

    FACE CLASSIFICATION FOR AUTHENTICATION APPROACH BY USING WAVELET TRANSFORM AND STATISTICAL FEATURES SELECTION by DAWOUD JADALAH, NADIR NOURAIN

    Published 2011
    “…In the last method, the Modified K-Means Algorithm was used to remove the non-face regions in the input image. …”
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    Thesis
  13. 13

    Modified Piecewise Linear Mapping Contrast Enhancement And Local Otsu Segmentation Methods For Hep-2 Cell Images by Baharom, Mohamad Shahrul Affendi

    Published 2019
    “…This study analyses the importance of both methods, which could possibly improve the HEP-2 classification process. …”
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    Thesis
  14. 14

    Feature extraction and classification stage on facial expression : A review by Shidiq, Muchamad Bachram, Ernawan, Ferda, Khubrani, Mousa Mohammed, Nugroho, Fajar Agung

    Published 2022
    “…This review will compare two kinds of extract features methods and one classification method. The first technique of extracting features is the optimization technique using the K-Mean algorithm, which helps to increase recognition accuracy. …”
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    Conference or Workshop Item
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    Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion by Zafar, R., Dass, S.C., Malik, A.S.

    Published 2017
    “…The proposed algorithm takes input data from multichannel EEG timeseries, which is also known as multivariate pattern analysis. …”
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    Article
  17. 17

    Development and performance of modified clay nanoporous pipe for subsurface irrigation by Abdullahi, Salisu

    Published 2021
    “…Supervised Classification method of Maximum Likelihood Algorithm in ArcGIS 10.7.1 software interface was used to analyse the images. …”
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    Thesis
  18. 18

    Quantitative spasticity assessment model of neurological disorder patients / AA Puzi … [et al.] by Ahmad Puzi, Asmarani, Aliff-Imran, M.D., Zainuddin, Ahmad Anwar, Basri, Atikah Balqis, Mohd Khairuddin, Ismail

    Published 2023
    “…The cues from the MMG signals pattern will be used to select the sampling features for the development of the classification algorithm model. …”
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    Book Section
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    A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification by Quteishat, A., Lim, C.P., Tan, K.S.

    Published 2010
    “…The first stage consists of a modified fuzzy min-max (FMM) neural-network-based pattern classifier, while the second stage consists of a genetic-algorithm (GA)-based rule extractor. …”
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    Article