Search Results - pattern extraction ((((method algorithm) OR (bees algorithm))) OR (path algorithm))

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  1. 1
    Feature extraction: hand shape, hand position and hand trajectory path

    Feature extraction: hand shape, hand position and hand trajectory path by Bilal, Sara Mohammed Osman Saleh, Akmeliawati, Rini

    Published 2011
    “…Algorithms have been developed for extracting these features after segmenting the head and the two hands. …”
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  2. 2
    NN with DTW-FF Coefficients and Pitch Feature for Speaker Recognition

    NN with DTW-FF Coefficients and Pitch Feature for Speaker Recognition by Sudirman, Rubita, Salleh, Sh-Hussain, Salleh, Shaharuddin

    Published 2006
    “…This paper proposes a new method to extract speech features in a warping path using dynamic programming (DP). …”
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  3. 3
    Artificial Bee Colony With Differential Evolution Algorithm For Feature Extraction And Selection Of Mass Spectrometry Data

    Artificial Bee Colony With Differential Evolution Algorithm For Feature Extraction And Selection Of Mass Spectrometry Data by Mohamed Yusoff, Syarifah Adilah

    Published 2016
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  4. 4
    Local DTW coefficients and pitch feature for back-propagation NN digits recognition

    Local DTW coefficients and pitch feature for back-propagation NN digits recognition by Sudirman, R., Salleh, Shahruddin Hussain, Salleh, Sh-Hussain

    Published 2006
    “…This paper presents a method to extract existing speech features in dynamic time warping path which originally was derived from LPC. …”
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  5. 5
    Local DTW Coefficients and Pitch Feature for Back-Propagation NN Digits Recognition

    Local DTW Coefficients and Pitch Feature for Back-Propagation NN Digits Recognition by Sudirman, Rubita, Salleh, Sh-Hussain, Salleh, Shaharuddin

    Published 2006
    “…This paper presents a method to extract existing speech features in dynamic time warping path which originally was derived from LPC. …”
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  6. 6
    Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm

    Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm by Sulaiman, Suriani, Ahmed Yahya, Saba, Mohd Shukor, Nur Sakinah, Ismail , Amelia Ritahani, Zaahirah, Qazi, Yaacob, Hamwira, Abdul Rahman, Abdul Wahab, Dzulkifli, Mariam Adawiah

    Published 2015
    “…This study aims at analyzing EEG signals for the purpose of clustering natural language morphemes using the Artificial Bee Colony (ABC) algorithm. Using as input the features extracted from EEG signals during morphological priming tasks, our experimental results indicate that applying the ABC algorithm on EEG datasets to cluster Malay morphemes produces promising results.…”
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  7. 7
    Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm

    Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm by Sulaiman, Suriani, Ahmed Yahya, Saba, Mohd Shukor, Nur Sakinah, Ismail , Amelia Ritahani, Zaahirah, Qazi, Yaacob, Hamwira Sakti, Abdul Rahman, Abdul Wahab, Dzulkifli, Mariam Adawiah

    Published 2015
    “…This study aims at analyzing EEG signals for the purpose of clustering natural language morphemes using the Artificial Bee Colony (ABC) algorithm. Using as input the features extracted from EEG signals during morphological priming tasks, our experimental results indicate that applying the ABC algorithm on EEG datasets to cluster Malay morphemes produces promising results.…”
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  8. 8
    Intelligent road recognition system for automous vehicle

    Intelligent road recognition system for automous vehicle by Soon, Adrian Bee Toing

    Published 2013
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  9. 9
    Finger Vein Recognition Using Pattern Map As Feature Extraction

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

    Published 2012
    “…This shows that pattern map is a reliable feature extraction method and is able to represent finger vein pattern effectively.…”
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  10. 10
    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier

    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
    “…Classic local binary pattern (LBP) is one of the most useful feature extraction methods. …”
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  11. 11
    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC

    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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  12. 12
    Social media mining: a genetic based multiobjective clustering approach to topic modelling

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

    Published 2021
    “…As the components of big data continue to expand, the task of extracting useful information becomes critical. Topic extraction refers to the process of extracting main topics from the pool of news feed and a typical method to perform topic extraction is through clustering. …”
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  13. 13
    Animal voice recognition for identification (ID) detection system

    Animal voice recognition for identification (ID) detection system by Yeo, Che Yong, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Ng, Chee Kyun

    Published 2011
    “…While the voice pattern classification will be done by using DTW algorithm. …”
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  14. 14
    Dog voice identification (ID) for detection system

    Dog voice identification (ID) for detection system by Yeo, Che Yong, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Ng, Chee Kyun

    Published 2012
    “…While the voice pattern classification will be done by using DTW algorithm. …”
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  15. 15
    Data normalization techniques in swarm-based forecasting models for energy commodity spot price

    Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

    Published 2014
    “…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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  16. 16
    Abnormal Pattern Detection In Ppg Signals Using Time Series Analysis

    Abnormal Pattern Detection In Ppg Signals Using Time Series Analysis by Siti Nur Hidayah, Mazelan

    Published 2022
    “…This project’s objectives are to implement rule-based algorithm method for abnormal pattern detection in PPG signals, and to investigate the accuracy and performance of rule-based algorithm in detecting the abnormal pattern. …”
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  17. 17
    Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin

    Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin by Shamsudin, Farah Syadiyah

    Published 2017
    “…Further studies can be made by using the same algorithm, but focusing more on the image enhancement and the feature extraction methods to improve the quality of the extraction of fingerprints.…”
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  18. 18
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

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

    Published 2017
    “…However, further study is needed in the feature extraction and clustering algorithms part as the performance of the pattern classification is still depending on the data input.…”
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  19. 19
    Temporal - spatial recognizer for multi-label data

    Temporal - spatial recognizer for multi-label data by Mousa, Aseel

    Published 2018
    “…Experiments on five datasets were conducted to compare the proposed method (imHTM) against statistical, template and structural pattern recognition methods. …”
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  20. 20
    Social media mining: a genetic based multiobjective clustering approach to topic modelling

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

    Published 2021
    “…As the components of big data continue to expand, the task of extracting useful information becomes critical. Topic extraction refers to the process of extracting main topics from the pool of news feed and a typical method to perform topic extraction is through clustering. …”
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