Search Results - (( pattern classification using algorithm ) OR ( using combination using 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

    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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  2. 2
    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
    “…On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. …”
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  3. 3
    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak

    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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  4. 4
    Classification for large number of variables with two imbalanced groups

    Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

    Published 2020
    “…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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  5. 5
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    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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  6. 6
    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm

    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

    Published 2023
    “…The purpose of choosing parameters is to get the best generalization performance. Genetic Algorithm (GA) is used to search for the best parameter of SVM classification by using combination of random and pre-populated genomes from Pre-Populated Database (PPD). …”
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  7. 7
    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks

    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

    Published 2014
    “…Firstly is by enhancing the learning algorithm of a neural-fuzzy network; and secondly by devising an ensemble model to combine the predictions from multiple neural-fuzzy networks using an agent-based framework. …”
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  8. 8
    An improved multiple classifier combination scheme for pattern classification

    An improved multiple classifier combination scheme for pattern classification by Abdullah,

    Published 2015
    “…Combining multiple classifiers are considered as a new direction in the pattern recognition to improve classification performance. …”
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  9. 9
    Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi

    Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi by Rahimi, Ahmad Faris

    Published 2017
    “…This indicates that the performance of KNN is acceptable and promising in this classification problem. Since KNN is the simplest form of artificial intelligence, future work could combine this algorithm with other classification algorithm. …”
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  10. 10
    Evaluation and optimization of frequent association rule based classification

    Evaluation and optimization of frequent association rule based classification by Izwan Nizal Mohd Shaharanee, Jastini Jamil

    Published 2014
    “…Empirical results show that with a proper combination of data mining and statistical analysis, the framework is capable of eliminating a large number of non-significant, redundant and contradictive rules while preserving relatively valuable high accuracy and coverage rules when used in the classification problem. …”
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  11. 11
    Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida

    Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida by Nanyonga , Aziida

    Published 2019
    “…Prediction, identification, understanding and visualization of relationship between factors affecting mortality in ACS patients using feature selection and ML algorithms. Feature selection, classification and pattern recognition methods have been used in this research. …”
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  12. 12
    Application of the bees algorithm to the selection features for manufacturing data

    Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

    Published 2007
    “…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
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  13. 13
    Design of intelligent Qira’at identification algorithm

    Design of intelligent Qira’at identification algorithm by Kamarudin, Noraziahtulhidayu

    Published 2017
    “…To evaluate the algorithm, 350 samples for 10 types of Qira’at recitation are in used, and for justifying the best pattern classification, few algorithms are tested in the early preliminary evaluation with K-Nearest Neighbour, GMM and PPCA. …”
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  14. 14
    Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal

    Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal by Fadzal, Ahmad Nazmi

    Published 2017
    “…Based on the concept, pheromone saturation is used to combine stackable solution pattern that is discovered while straying to different term node to build a path. …”
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  15. 15
    Diabetic Retinopathy Detection Model using Hybrid of U-Net and Vision Transformer Algorithms

    Diabetic Retinopathy Detection Model using Hybrid of U-Net and Vision Transformer Algorithms by Mudit, Khater

    Published 2024
    “…Now, we present a hybrid model which is a combination of U-Net algorithm used for image segmentation and Vision Transformer for classification. …”
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  16. 16
    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
    “…Hence, this work aims to develop an algorithm using statistical-CSP feature for eye state classification from EEG signal. …”
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  17. 17
    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
    “…Hence, this work aims to develop an algorithm using statistical-CSP feature for eye state classification from EEG signal. …”
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  18. 18
    Brain machine interfaces: recognition of mental tasks using neural networks and PSO learning algorithms / Hema C.R. ...[et al.]

    Brain machine interfaces: recognition of mental tasks using neural networks and PSO learning algorithms / Hema C.R. ...[et al.] by C.R., Hema, M.P., Paulraj, Yaacob, S., Adom, A.H., R., Nagarajan

    Published 2009
    “…Two neural network architectures using a novel particle swarm optimization (PSO) learning algorithm is studied. …”
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  19. 19
    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network

    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

    Published 2016
    “…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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  20. 20
    Waste classification using support vector machine with SIFT-PCA feature extraction

    Waste classification using support vector machine with SIFT-PCA feature extraction by Puspaningrum, Adita Putri, Endah, Sukmawati Nur, Sasongko, Priyo Sidik, Kusumaningrum, Retno, ., Khadijah, ., Rismiyati, Ernawan, Ferda

    Published 2020
    “…The data used in this research is Trashnet datasets. The performance of the SVM classification using SIFT feature is compared with the similar algorithm with SIFT-PCA combined feature. …”
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