Search Results - (( using normalization _ algorithm ) OR ( pattern classification based algorithm ))

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  1. 1

    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
    “…In this project, a classification system is proposed with the one-dimensional local binary pattern algorithm (1D-LBP) with the K-Nearest Neighbour (K-NN) classifier and the system is developed by using a Raspberry Pi 3.There are eight different subjects used to classify in this classification system and each subject consists of seven samples of normalized iris image as input to the system. …”
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    Monograph
  2. 2

    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
  3. 3

    Classification of Emphysema Patterns in Computed Tomography Based On Gabor Filter by Tengku Azis, Tengku Mohd Syamim

    Published 2015
    “…The images obtained from different slices are then used by radiologist to identify normal or abnormal tissues. …”
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    Final Year Project
  4. 4

    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
  5. 5

    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
  6. 6

    Neural network paradigm for classification of defects on PCB by Heriansyah, Rudi, Syed Al-Attas, Syed Abdul Rahman, Zabidi, Muhammad Mun'im Ahmad

    Published 2003
    “…A new technique is proposed to classify the defects that could occur on the PCB using neural network paradigm. The algorithms to segment the image into basic primitive patterns, enclosing the primitive patterns, patterns assignment, patterns normalization, and classification have been developed based on binary morphological image processing and Learning Vector Quantization (LVQ) neural network. …”
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    Article
  7. 7

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

    Published 2019
    “…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
  8. 8

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

    Published 2019
    “…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
  9. 9

    Converged Classification Network For Matching Cost Computation by Hamid, Mohd Saad, Abd Manap, Nurulfajar, Hamzah, Rostam Affendi, Kadmin, Ahmad Fauzan

    Published 2020
    “…Overall quantitative results for the proposed work performed competitively compared to other established stereo matching algorithm based on the Middlebury standard benchmark online system.…”
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    Article
  10. 10

    VGG16-based deep learning architectures for classification of lung sounds into normal, crackles, and wheezes using Gammatonegrams by Zakaria, Neili, Sundaraj, Kenneth

    Published 2023
    “…Breathing sounds are a rich source of information that can assist doctors in diagnosing pulmonary diseases in a non-invasive manner. Several algorithms can be developed based on these sounds to create an automatic classification system for lung diseases. …”
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    Conference or Workshop Item
  11. 11

    Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

    Published 2015
    “…With respect to all the algorithms, V-Detector proved to be superior and surpassed all other algorithms based on performance and execution time.…”
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    Thesis
  12. 12

    Improved Genetic Algorithm Multilayer Perceptron Network For Data Classification by Ahmad, Fadzil

    Published 2017
    “…Based on the occurrences of the best result obtained by an algorithm across different test functions; it is proven that the proposed method outperforms standard GA. …”
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    Thesis
  13. 13
  14. 14

    Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm by Acharya, U.R., Faust, O., Molinari, F., Sree, S.V., Junnarkar, S.P., Sudarshan, V.

    Published 2015
    “…We then review the state-of-the-art US-based CAD techniques that utilize a range of image texture based features like entropy, Local Binary Pattern (LBP), Haralick textures and run length matrix in several automated decision making algorithms. …”
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    Article
  15. 15

    Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin by Shamsuddin, Noraishah

    Published 2011
    “…A Lipschitz method and Leven berg Marquardt algorithm is used to determine the model order number and train the network respectively. …”
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    Thesis
  16. 16

    Handgrip strength evaluation using neuro fuzzy approach by Seng, W.C., Chitsaz, M.

    Published 2010
    “…The purpose of this study is to collect handgrip strength of patients and distinguish them from the normal persons. Multilevel Perception neural network utilizes the back-propagation learning algorithm is suitable to discover relationships and patterns in the dataset. …”
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    Article
  17. 17

    Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network by Al-Hiyali, M.I., Yahya, N., Faye, I., Hussein, A.F.

    Published 2021
    “…Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. …”
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    Article
  18. 18

    Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network by Al-Hiyali, M.I., Yahya, N., Faye, I., Hussein, A.F.

    Published 2021
    “…Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. …”
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    Article
  19. 19

    A novel selection of optimal statistical features in the DWPT domain for discrimination of ictal and seizure-free electroencephalography signals by Ong, Pauline, Zainuddin, Zarita, Kee, Huong Lai

    Published 2018
    “…Instead of using the complete set of the extracted features to construct a wavelet neural networks-based classifer, an optimal feature subset that maximizes the predictive competence of the classifer was selected by using the CSA. …”
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    Article
  20. 20

    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia by San, Limhwee

    Published 2006
    “…The objective of this study is to develop an algorithm based on the aerosol optical thickness (AOT) for mapping PM1 0 using digital camera and satellite imageries. …”
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    Thesis