Principle component Analysis (PCA)
Speech Enhancement in Wavelet Domain using Principle Component Analysis and Enhancement Filters
... The aim of speech enhancement is to improve the perceptual quality and intelligibility of the speech by reducing the background noise. This paper proposes a technique in wavelet domain to enhance the signal. The signal ...
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Anomaly network intrusion detection method in network security based on principle component analysis
... Principle Component Analysis (PCA, also called Karhunen-Loeve transform) is one of the most widely used dimension reduction techniques for data analysis and compression in ...image ...
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Hyperspectral Images Classification via Weighted Spatial Spectral Principle Component Analysis
... Information Principle Component Analysis PCA, a classical and effective method for feature extraction, can reduce the correlation between HSI data by using several principal components which are ...
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Celiac Disease Seen with the Eyes of the Principle Component Analysis and Analyse Des Données
... the principle component analysis (pca) and the Analyse des Données to further study the risk [7] [8] and therefore dietary transgression (Figure ...
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A Comparative Study on using Principle Component Analysis with different Text Classifiers
... Principle component analysis (PCA) is one of the most popular sta- tistical technique for feature ...the principle components is less than or equal to the number of the original fea- ...
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Efficient Image Recognition Technique Using Invariant Moments and Principle Component Analysis
... Image recognition is widely used in different application areas such as shape recognition, gesture recognition and eye recognition. In this research, we in- troduced image recognition using efficient invariant moments ...
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Weighted Principle Component Analysis For Dimensionality Reduction In Medical Dataset
... simultaneously. Principle Component Analysis (PCA) is a standard technique for dimensionality reduction and has been applied to a large ...Principal Component Analysis is used to ...
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A Effective Disease Prediction Model Using Enhanced Principle Component Analysis And Mdrp Algorithm
... data analysis plays an important ...Enhanced Principle Component Analysis to improve the Disease prediction accuracy and to investigate the risk level of the ...
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Metabolite Profiling and Principle Component Analysis of a Mangrove Plant Aegiceras Corniculatum L (Blanco)
... The analysis of PCA components generated in data sets showed the principal components of water, Methanolic extracts of leaves and bark (WB, WL, MB, ML) were clustered together while the Petroleum ether components ...
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Sentimental Analysis of Tweets using Principle Component Analysis Technique
... PCA is the very useful technique for data reduction in Sentimental Analysis in view to deciding the real approach of reviews PCA is applied on 2000 tweets related to iPhone 7 to find the reliability of tweets. In ...
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Face Recognition using Eigenvector and Principle Component Analysis
... PCA is one of the most successful techniques that have been used in face recognition. The objective of the Principal Component Analysis is to take the total variation on the training set of faces and to ...
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Face Recognition using Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA)
... The goal of the Linear Discriminant Analysis (LDA) is to find an efficient way to represent the face vector space. PCA constructs the face space using the whole face training data as a whole, and not using the ...
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Motion Classification Using Proposed Principle Component Analysis Hybrid K Means Clustering
... This study investigates and acts as a trial clinical outcome for human motion and behaviour analysis in consensus of health related quality of life in Malaysia. The proposed technique was developed to analyze and ...
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Parallel Filtration Based on Principle Component Analysis and Nonlocal Image Processing
... Abstract —It is common that typical devices that form digital images contain of lenses and semiconducting sensors which capture a projected scene. These components cause distortions such as simple geometrical distortion, ...
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File Security Using Principle Component Analysis Induced Facial Recognition
... Modified component analysis showed significant levels of increase in the recognition accuracy over a training set of ten people with random training images and test images varying from Straight, Tilted, ...
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Assessment of Genotype-Environment Interaction Using Additive Main Effects and Multiplicative Interaction Model (AMMI) in Maize (Zea mays L.) Hybrids
... statistical analysis is not always effective with this data structure (Zobel, et ...(Principle component analysis) is a multiplicative model and hence contain no sources for additive genotype ...
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Classification of Landsat 8 Imagery Based On Pca And Ndvi Methods
... In this work satellite image which acquired with Landsat 8 is classified by combining NDVI and Principle component analysis in order to improve the classification accuracy. The results are compared ...
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Gloves Gesture Recognition
... The acquired highlights are thought about by utilizing Principle Component Analysis (PCA) calculation. In the wake of contrasting highlights of caught sign and test[r] ...
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Wavelet Transform Based Face Recognition Using SURF Descriptors
... Later Principle Component Analysis (PCA) [3] and Linear Discriminant Analysis (LDA) [4] based algorithms were ...subspace analysis and view manifold modeling [6], Local Fisher ...
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Face Recognition Techniques: A Survey
... (LBP), Principle Component Analysis (PCA), Elastic Bunch Graph Matching, Linear Discriminant Analysis (LDA) and Histogram of Oriented Gradient (HOG) which are used for face ...
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