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1
A Comparison Study On Pca_Modular Pca And Lda For Face Recognition
Published 2017“…This paper will study the performance of three face recognition algorithms which are PCA, Modular PCA and LDA. These three face recognition algorithms will be implement to determine which algorithm has the best performance. …”
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Monograph -
2
Improved clustering using robust and classical principal component
Published 2017“…The classical k-means algorithm and the k-means by PCA algorithm are very sensitive to the presence of outlier. …”
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3
Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…The developed algorithm weighted the n objects contribution in explaining the separation between groups. …”
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4
Algorithm for rapid identification of flavonoids classes
Published 2017“…The study concluded that FTIR coupled with PCA analysis can be used as a molecular fingerprint for rapid identification of flavonoids.…”
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5
Characterization And Classification Of Bioactive Compound In Natural Products By FTIR And Multivariate Data Analysis
Published 2018“…Fourier Transform Infrared (FTIR) spectroscopy coupled with multivariate statistical data analysis, which is Principal Component Analysis (PCA) was performed. The results showed that the flavonoids classes were identified according to spectral region assigned using the PCA algorithm based on the FTIR spectrum of the samples. …”
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Monograph -
6
A region-based Principal Component Analysis (PCA) technique for medical image compression
Published 2022“…The research has successfully developed an improved region-based compression scheme for medical images where lossy and lossless compression is implemented in one PCA architecture. …”
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7
Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models
Published 2023“…The data for training and testing the algorithms was derived using the regression equation developed using the Box-Behnken Design (BBD). …”
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8
Application of multivariate data analysis for rapid identification of flavonoids classes
Published 2016“…Fourier Transform Infrared (FTIR) spectroscopy coupled with multivariate statistical data analysis, which is Principal Component Analysis (PCA) was performed. The results showed that the flavonoids classes were identified according to spectral region assigned using the PCA algorithm based on the FTIR spectrum of the samples. …”
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Proceeding Paper -
9
Optimized clustering with modified K-means algorithm
Published 2021“…In dealing with correlated variables, PCA was embedded in the proposed algorithm. The developed algorithms were tested on uncorrelated and correlated simulated data sets, generated under various conditions. …”
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10
Disposable Biomimetic Array Sensor Strip Coupled With Chemometric Algorithm For Quality Assessment Of Orthosiphon Stamineus Benth Samples
Published 2006“…The classification model built with PCA was useful for the discrimination of the herb according to its parts; stem and leaves, while was also successfully applicable for different type of O.stamineus extracts identification. …”
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11
Raspberry Pi-Based Finger Vein Recognition System Using PCANet
Published 2018“…A comparison between PCANet and PCA shows that PCANet is outperform under limited training samples, with an increase of 21.3% than that of PCA. …”
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Monograph -
12
Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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13
Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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14
Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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15
Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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16
Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2023“…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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17
A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm
Published 2024“…This research employed a modified version of the Design Science Research Methodology (DSRM), streamlined into five stages: problem identification, theoretical study, framework development, evaluation, and reporting. …”
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18
Development of algorithm to characterize flavonoids classes
Published 2017“…Development of algorithm based on PCA for the analysis and identification of flavonoids classes based on FTIR spectrum is introduced. …”
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Proceeding Paper -
19
Natural image noise level estimation based on local statistics for blind noise reduction
Published 2018“…Consequently, we need to estimate the noise level from the selected patches using principal component analysis (PCA). For blind denoising applications, the proposed denoising algorithm integrates the undecimated wavelet-based denoising algorithms and PCA to develop the subjective and objective qualities of the observed image, which result from filtering processes. …”
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20
Minimum regularized covariance determinant and principal component analysis-based method for the identification of high leverage points in high dimensional sparse data
Published 2022“…A simulation study and two real data sets are used to illustrate the merit of our proposed method compared to the RMD-MRCD and Robust PCA (ROBPCA) methods. …”
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