Search Results - (( pattern classification methods algorithm ) OR ( process identification method algorithm ))

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  1. 1
    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
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  2. 2
    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
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  3. 3
    Finger Vein Recognition Using Pattern Map As Feature Extraction

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

    Published 2012
    “…Experimental results show that the proposed pattern map algorithm has better performance with a consistent identification rate of 99% and above compared to existing methods such as PCA and Gabor with FVCode. …”
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    Thesis
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  4. 4
    Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari

    Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari by Sha’ari, Nor Silawati

    Published 2018
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  5. 5
    Sistem Pengecaman Bentuk Berdasarkan FPGA

    Sistem Pengecaman Bentuk Berdasarkan FPGA by Zainal Ariffin, Nur Bayani

    Published 2005
    “…Pattern recognition means that the definition, identification and the classification by deciding the characteristics of that pattern which is need to be known. …”
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    Monograph
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  6. 6
    Red blood cells classification with sharpening segmentation and mask R-CNN

    Red blood cells classification with sharpening segmentation and mask R-CNN by Arianti, Nunik Destria, Muda, Azah Kamilah, Ahmad, Norashikin

    Published 2023
    “…Eventually, the RBCs were classified as overlapping or single RBCs using the mask R-CNN classifier algorithm. In this study, a combination of 3 preprocessing image methods, including sharpening with the wand library, clahe, and the Otsu threshold, was used. …”
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  7. 7
    CORROSION DAMAGE ANALYSIS USING IMAGE PROCESSING

    CORROSION DAMAGE ANALYSIS USING IMAGE PROCESSING by DEMPI, CHRISTIE BANGI

    Published 2018
    “…This project will analyze the texture feature extraction techniques, select and apply the most appropriate technique to corrosion detection problem. The corrosion pattern is to be classified by applying neural network algorithm. …”
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    Final Year Project
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  8. 8
    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan

    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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  9. 9
    Identification model for hearing loss symptoms using machine learning techniques

    Identification model for hearing loss symptoms using machine learning techniques by Nasiru Garba Noma

    Published 2014
    “…The model is implemented using both unsupervised and supervised machine learning techniques in the form of Frequent Pattern Growth (FP-Growth) algorithm as feature transformation method and multivariate Bernoulli naïve Bayes classification model as the classifier. …”
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  10. 10
    Maize leaf disease detection and classification using Convolutional Neural Network (CNN) / Syafiqah Amir

    Maize leaf disease detection and classification using Convolutional Neural Network (CNN) / Syafiqah Amir by Amir, Syafiqah

    Published 2023
    “…Implementing prompt and focused management methods for these disorders requires early identification and correct diagnosis. …”
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  11. 11
    A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar

    A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar by Noorsal, Emilia, Osman, Muhammad Khusairi, Mokhtar, Norfadzilah

    Published 2007
    “…It is well known that the use of a gas sensor array and pattern recognition system offers an effective technique for the identification of volatile organic molecules because of the poor selectivity of a lot of other gas sensors. …”
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    Research Reports
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  12. 12
    APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN

    APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN by SARI, YUNITA SARI

    Published 2011
    “…The Self-Training algorithm greatly benefits semi-supervised learning which allows classification of entities given only a small-size of labelled data. …”
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  13. 13
    Integrated framework with association analysis for gene selection in microarray data classification

    Integrated framework with association analysis for gene selection in microarray data classification by Ong, Huey Fang

    Published 2011
    “…However, most of the existing gene selection methods are statistical analyses and purely based on gene expression values in the identification of differentially expressed genes. …”
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  14. 14
    Finger-Vein Biometric Identification Using Convolutional Neural Network

    Finger-Vein Biometric Identification Using Convolutional Neural Network by Syafeeza, Ahmad Radzi, Mohamed, Khalil-Hani, Rabia, Bakhteri

    Published 2016
    “…In conventional finger-vein recognition methods, complex image processing is required to remove noise and extract and enhance the features before the image classification can be performed in order to achieve high performance accuracy. …”
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  15. 15
    Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions

    Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Al-Garadi, Mohammed Ali

    Published 2019
    “…These sensors are pre-processed and different feature sets such as time domain, frequency domain, wavelet transform are extracted and transform using machine learning algorithm for human activity classification and monitoring. …”
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  16. 16
    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
    “…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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  17. 17
    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
    “…There are a lot of feature extraction methods and classification methods for iris classification. …”
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    Monograph
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  18. 18
    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…This method carries the advantages of the two previous methods in order to improve the classification tasks. …”
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  19. 19
    Pattern Recognition for Human Diseases Classification in Spectral Analysis

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

    Published 2022
    “…Typically, pattern recognition consists of two components: exploratory data analysis and classification method. …”
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  20. 20
    The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition

    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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