Search Results - (( using function method algorithm ) OR ( pattern classification means algorithm ))

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  1. 1

    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
  2. 2

    Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

    Published 2005
    “…At the core of our system is a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data non-linearly separable in input space. …”
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    Article
  3. 3

    Correlation-based common spatial pattern (CCSP): A novel extension of CSP for classification of motor imagery signal by Khatereh Darvish ghanbar, Tohid Yousefi Rezaii, Ali Farzamnia, Ismail Saad

    Published 2021
    “…The simulation results showed that the proposed method outperformed conventional CSP by 6.9% in 2-class and 2.23% in multi-class problem in term of mean classification accuracy.…”
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    Article
  4. 4

    Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition by Burhan, Nuradebah

    Published 2018
    “…Subsequently,the filtered signal containing useful information was extracted by three methods  root mean square (RMS),mean absolute value (MAV),and autoregressive (AR) covariance,all of which are commonly used in TD.A comparative analysis of the three different techniques was performed based on the accuracy performance of the EMG pattern classification using linear vector quantization (LVQ) neural network.In the experimental work undertaken,six healthy subjects comprised of males and females were selected. …”
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    Thesis
  5. 5

    A framework for predicting oil-palm yield from climate data by Awan, A. Majid, Md. Sap, Mohd. Noor

    Published 2006
    “…At the core of our system is a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data. …”
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    Conference or Workshop Item
  6. 6

    Face emotion recognition using artificial intelligence techniques by Kartigayan Muthukaruppan

    Published 2008
    “…In the case of second classification technique, two forms of fuzzy c-mean clustering are considered and their performances are compared. …”
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    Thesis
  7. 7

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

    Published 2012
    “…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
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    Thesis
  8. 8

    Adaptive resonance theory-based hand movement classification for myoelectric control system by Fariman, Hessam Jahani

    Published 2014
    “…First evaluation considers the investigation of feature extraction method; where the proposed multi-feature consisting of Mean Absolute Value (MAV), Zero Crossing (ZC), Waveform Length (WL), Slope Sign Change (SSC), Root Mean Square (RMS), and Mean Frequency (MNF) has been compared to 2 well-known high accuracy and simple multi-feature methods. …”
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    Thesis
  9. 9

    A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

    Published 2004
    “…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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    Monograph
  10. 10

    Firearm recognition based on whole firing pin impression image via backpropagation neural network by Ahmad Kamaruddin, Saadi, Md Ghani, Nor Azura, Liong, Choong-Yeun, Jemain, Abdul Aziz

    Published 2011
    “…A two-layer 6-7-5 connections BPNN of sigmoid/linear transfer functions with ‘trainlm’ algorithm was found to yield the best classification result using cross-validation, where 96% of the images were correctly classified according to the pistols used. …”
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    Book Chapter
  11. 11

    Firearm recognition based on whole firing pin impression image via backpropagation neural network by Ahmad Kamaruddin, Saadi, Md Ghani, Nor Azura, Liong, Choong-Yeun, Jemain, Abdul Aziz

    Published 2011
    “…A two-layer 6-7-5 connections BPNN of sigmoid/linear transfer function with ‘trainlm’ algorithm was found to yield the best classification result using cross-validation, where 96% of the images were correctly classified according to the pistols used. …”
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    Proceeding Paper
  12. 12

    Pattern Classification of Human Epithelial Images by Mohd Isa, Mohd Fazlie

    Published 2016
    “…Last but not least, from the mean of properties, it will classify into the pattern after ranging the value of mean properties of each of the pattern itself that has been done in classification stage.…”
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    Final Year Project
  13. 13

    Artificial neural network implementation on firearm recognition system with respect to ring firing pin impression image by Ahmad Kamaruddin, Saadi, Md Ghani, Nor Azura, Liong, Choong-Yeun, Jemain, Abdul Aziz

    Published 2011
    “…A two-layer 6-7-5 connections BPNN of sigmoid/sigmoid transfer functions with ‘trainscg’ algorithm was found to yield the best classification result using cross-validation, where 98% of the images were correctly classified according to the pistols used. …”
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    Proceeding Paper
  14. 14

    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
  15. 15

    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, khan

    Published 2011
    “…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
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    Citation Index Journal
  16. 16
  17. 17

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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    Article
  18. 18

    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
  19. 19

    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

    Published 2002
    “…That is, to use training speech patterns to generate classification rules that can be used later to classify input words patterns. …”
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    Thesis
  20. 20

    Biceps brachii surface EMG classification using neural networks by Chong, Yee Lin

    Published 2012
    “…The experimental results show that EMG signals of different biceps activity is differed and simple statistical features are sufficient to represent the EMG pattern. The proposed BPN with Levenberg-Marquardt (LM) algorithm and PNN had achieved an overall classification rate of 88% while BPN with Resilient-Propagation (RP) algorithm achieved an overall classification of 87.11%. …”
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    Thesis