Search Results - (( pattern extraction method algorithm ) OR ( data selection methods algorithm ))

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  1. 1
    Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion

    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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  2. 2
    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat

    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

    Published 2021
    “…Readability was detected using a free online optical character recognition application called Aeosoft. Size was extracted using Extreme Point Detection algorithm and Hit or Miss Transformation method was used to extract the stroke formation pattern. …”
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  3. 3
    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network

    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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  4. 4
    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection

    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

    Published 2020
    “…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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  5. 5
    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter

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

    Published 2019
    “…The process of developing the EEG eye state classification algorithm, includes data extraction, pre-processing, data normalization, feature extraction, feature selection and classification are detailed out in this paper. …”
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  6. 6
    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter

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

    Published 2019
    “…The process of developing the EEG eye state classification algorithm, includes data extraction, pre-processing, data normalization, feature extraction, feature selection and classification are detailed out in this paper. …”
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  7. 7
    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani

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

    Published 2016
    “…Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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  8. 8
    The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN

    The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN by Rashid, Mamunur, Bari, Bifta Sama, Hasan, Md Jahid, Mohd Azraai, Mohd Razman, Rabiu Muazu, Musa, Ahmad Fakhri, Ab. Nasir, Anwar, P. P. Abdul Majeed

    Published 2021
    “…The common spatial pattern (CSP) has been applied to extract the features from the MI response, and the effectiveness of random forest (RF)-based feature selection algorithm has also been investigated. …”
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  9. 9
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…There are many algorithm for analysing clustering each having its own method to do clustering. …”
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  10. 10
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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  11. 11
    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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  12. 12
    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods

    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Audrey Huong, Kim Gaik Tay, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

    Published 2023
    “…This work compared manual segmentation with our proposed hybrid automatic segmentation method (HHM) for this classification problem. Methods: Manual segmentation involved selecting a region-ofinterest (ROI) in images from the Bosphorus dataset to generate ground truth data. …”
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  13. 13
    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods

    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Audrey Huong, Kim Gaik Tay, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

    Published 2023
    “…This work compared manual segmentation with our proposed hybrid automatic segmentation method (HHM) for this classification problem. Methods: Manual segmentation involved selecting a region-ofinterest (ROI) in images from the Bosphorus dataset to generate ground truth data. …”
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  14. 14
    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals

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

    Published 2020
    “…The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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  15. 15
    EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique

    EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique by Liew, Siaw Hong

    Published 2016
    “…The correlation-based feature selection (CFS) method was used to select representative WPD vector subset to eliminate redundancy before combining with other features. …”
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  16. 16
    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods

    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Kim Gaik Tay, Audrey Huong, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

    Published 2023
    “…This work compared manual segmentation with our proposed hybrid automatic segmentation method (HHM) for this classification problem. Methods: Manual segmentation involved selecting a region-ofinterest (ROI) in images from the Bosphorus dataset to generate ground truth data. …”
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  17. 17
    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods

    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Audrey Huong, Kim Gaik Tay, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

    Published 2023
    “…This work compared manual segmentation with our proposed hybrid automatic segmentation method (HHM) for this classification problem. Methods: Manual segmentation involved selecting a region-ofinterest (ROI) in images from the Bosphorus dataset to generate ground truth data. …”
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  18. 18
    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods

    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Kim Gaik Tay, Audrey Huong, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

    Published 2023
    “…This work compared manual segmentation with our proposed hybrid automatic segmentation method (HHM) for this classification problem. Methods: Manual segmentation involved selecting a region-ofinterest (ROI) in images from the Bosphorus dataset to generate ground truth data. …”
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  19. 19
    Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction

    Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction by Al-Himyari, Bayadir Abbas

    Published 2017
    “…A fitness function is proposed to deal with multi-objective problem without weight using a new composition method. The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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  20. 20
    Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients

    Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

    Published 2017
    “…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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