Search Results - (( pattern classification methods algorithm ) OR ( _ classification using algorithm ))

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  1. 1

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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    Thesis
  2. 2

    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
    “…There are a lot of feature extraction methods and classification methods for iris classification. …”
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    Monograph
  3. 3

    Pattern Recognition for Human Diseases Classification in Spectral Analysis by Nur Hasshima Hasbi, Abdullah Bade, Fuei, Pien Chee, Muhammad Izzuddin Rumaling

    Published 2022
    “…On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. …”
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    Article
  4. 4

    The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition by M. A., Ameedeen, Marhaini, M. S.

    Published 2016
    “…While the algorithm helped to classify different types of wavelengths produced from the sensor, a classification-based algorithm via Pattern Recognition Method will be used to classify and match the food components. …”
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    Conference or Workshop Item
  5. 5

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…It involves development of Max-Min Rule-Based Classification Algorithm. The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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    Thesis
  6. 6

    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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    Article
  7. 7

    Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification by Abusnaina, Ahmed A., Abdullah, Rosni

    Published 2013
    “…Traditional training algorithms have some drawbacks such as local minima and its slowness.Therefore, evolutionary algorithms are utilized to train neural networks to overcome these issues.This research tackles the ANN training by adapting Mussels Wandering Optimization (MWO) algorithm.The proposed method tested and verified by training an ANN with well-known benchmarking problems.Two criteria used to evaluate the proposed method were overall training time and classification accuracy.The obtained results indicate that MWO algorithm is on par or better in terms of classification accuracy and convergence training time.…”
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    Conference or Workshop Item
  8. 8

    Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm by Mohamed, M. E, Samir, B. B., Azween, Abdullah

    Published 2010
    “…In this work, we integrate artificial immune algorithm with non-linear classification of pattern recognition and machine learning methods to solve the problem of intrusion detection in network systems. …”
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    Citation Index Journal
  9. 9

    Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

    Published 2007
    “…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
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    Conference or Workshop Item
  10. 10

    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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    Final Year Project
  11. 11

    Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi by Rahimi, Ahmad Faris

    Published 2017
    “…This indicates that the performance of KNN is acceptable and promising in this classification problem. Since KNN is the simplest form of artificial intelligence, future work could combine this algorithm with other classification algorithm. …”
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    Thesis
  12. 12

    Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal by Fadzal, Ahmad Nazmi

    Published 2017
    “…ACO classification accuracy is compared to Genetic Algorithm classifier which also a wrapper method. …”
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    Thesis
  13. 13

    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

    Published 2014
    “…Pattern classification is one of the major components for the design and development of a computerized pattern recognition system. …”
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    Thesis
  14. 14

    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…The SNS classification model use negative selection and PSO algorithms to form a set of memory Artificial Lymphocytes (ALCs) that have the ability to distinguish between normal and epileptic EEG patterns. …”
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    Article
  15. 15

    Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

    Published 2016
    “…The aim of this article attempts to study the potential of this method in text classification for sentiment analysis.This study consists of three phases; data preparation; classification model development using three selected Immune System based algorithms i.e. …”
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    Conference or Workshop Item
  16. 16

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

    Published 2015
    “…The aim of data mining is to search and find undetermined patterns in huge databases. A well known task is classification that predicts the class of new instances using known features or attributes automatically. …”
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    Thesis
  17. 17

    Non-invasive pathological voice classifications using linear and non-linear classifiers by Hariharan, Muthusamy

    Published 2010
    “…Two types of experiments are conducted using the proposed feature extraction and classification algorithms. …”
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    Thesis
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    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

    Published 2019
    “…These indicate that both methods give good discrimination of the eye state condition but on it own, will not be sufficient to produce good classification accuracy. Hence, this work aims to develop an algorithm using statistical-CSP feature for eye state classification from EEG signal. …”
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    Conference or Workshop Item
  20. 20

    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

    Published 2019
    “…These indicate that both methods give good discrimination of the eye state condition but on it own, will not be sufficient to produce good classification accuracy. Hence, this work aims to develop an algorithm using statistical-CSP feature for eye state classification from EEG signal. …”
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    Conference or Workshop Item