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feature-extraction method

A New Unsupervised Clustering based Feature Extraction Method

A New Unsupervised Clustering based Feature Extraction Method

... unsupervised feature extraction, where no prior knowledge about pdfs of data or about its class-distribution is ...unsupervised feature extraction method is Principal Component Analysis ...

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A Chinese Product Feature Extraction Method Based on KNN Algorithm

A Chinese Product Feature Extraction Method Based on KNN Algorithm

... product feature extraction are mainly divided into two categories: manual definition and automatic ...learning method to extract product ...the extraction of opinion examples and es- tablished ...

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INFORMATION EXTRACTION FROM TEXT DOCUMENT USING PATTERN MINING AND FEATURE EXTRACTION METHOD

INFORMATION EXTRACTION FROM TEXT DOCUMENT USING PATTERN MINING AND FEATURE EXTRACTION METHOD

... of feature vector which is usually ...efficient feature extraction algorithms is highly needed to deal with high- dimensional data ...Typically feature extraction method aims to ...

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An On line Feature Extraction Method for Transformer Vibration Signals

An On line Feature Extraction Method for Transformer Vibration Signals

... a feature extraction method based on FFT and wavelet packet transform is ...this method, firstly, the characteristic frequency of the vibration signal is identify by FFT, then wavelet packet ...

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Hybrid Feature Extraction Method for Partial Face Recognition

Hybrid Feature Extraction Method for Partial Face Recognition

... Facial feature extraction is an important phase in a face recognition ...A feature extraction algorithm plays an important role in a face recognition ...facial feature extraction ...

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Sentiment Analysis on IMDb Movie Reviews Using Hybrid Feature Extraction Method

Sentiment Analysis on IMDb Movie Reviews Using Hybrid Feature Extraction Method

... Hybrid Feature Extraction Method (HFEM) is used to extract features from machine learning and lexicon based feature extraction ...The feature selection methods such as ...

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A Novel EEG Feature Extraction Method Using Hjorth Parameter

A Novel EEG Feature Extraction Method Using Hjorth Parameter

... BCI method uses electrodes placed on the exposed surface of a brain to record electrical ...noninvasive method does not need any surgical process although it suffers from low quality of measurement ...

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A novel feature extraction method by compressive sensing for signal peptide

A novel feature extraction method by compressive sensing for signal peptide

... the feature vector abstracted by CS was the optimal combination of the original information (amino acid composition, sequence order, and so ...new method can be regarded as a comprehensive development of ...

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A new kernel method for hyperspectral image feature extraction

A new kernel method for hyperspectral image feature extraction

... challenge. Feature extraction is a very important step for hyperspectral image ...processing. Feature extraction methods aim at reducing the dimension of data, while preserving as much ...

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Recognition of Bisindo Alphabets Based on Chain Code Contour and Similarity of Euclidean Distance

Recognition of Bisindo Alphabets Based on Chain Code Contour and Similarity of Euclidean Distance

... use feature extraction method using contour following and formation of chain code to identify patterns in BISINDO alphabets which they are not uniform or ...features extraction process used in ...

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Novel Method of FKP Feature Extraction Using Mechanical Variable

Novel Method of FKP Feature Extraction Using Mechanical Variable

... of feature extraction improves the supplementary processing of biometric image to an immense ...segmentation, extraction and classification techniques [4]. Feature extraction ...

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Cursive Handwriting Recognition System using Feature Extraction and Artificial Neural Network

Cursive Handwriting Recognition System using Feature Extraction and Artificial Neural Network

... The first step in any handwritten recognition system is pre- processing followed by segmentation and feature extraction. Pre-processing is mainly essential to shape the input image into a form suitable for ...

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Comparative study between feature extraction methods for face recognition

Comparative study between feature extraction methods for face recognition

... of feature extraction methods for appearance based are Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA) (Turk, ...a feature extraction method become one of ...

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SPECTRUM INVESTIGATION FOR SHARING ANALYSIS BETWEEN BWA SYSTEM AND FSS RECEIVER

SPECTRUM INVESTIGATION FOR SHARING ANALYSIS BETWEEN BWA SYSTEM AND FSS RECEIVER

... auto-correlogram method as color feature extraction method and Gray Level Co-occurrence Matrix (GLCM) method as texture feature extraction ...robust feature set for ...

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Optical Character Recognition

Optical Character Recognition

... A. Global thresholding is used to convert the input image in to bi-level form. Erosion, dilation and thinning are the morphological operations. To obtain the skeleton thinning is used. Line segmentation, word ...

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Vanishing Moments of a Wavelet System and Feature Set in Face Detection Problem for Color Images

Vanishing Moments of a Wavelet System and Feature Set in Face Detection Problem for Color Images

... threshold feature extraction method, it is found that using wavelets with higher order vanishing moment of the same family resulted in steady change in the number of feature ...of ...

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Research on the Fractal Feature Extraction Based SSVEP Idle-State Detection

Research on the Fractal Feature Extraction Based SSVEP Idle-State Detection

... of feature extraction method plays key ...non-linear feature extraction method employing fractal analysis ...fractal feature extraction method for SSVEP ...

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Review of Feature Selection Methods in Medical Image Processing

Review of Feature Selection Methods in Medical Image Processing

... continuous feature discretization and identified defining characteristics of the ...and feature selection to select the most relevant features which can be used for classification ...for feature ...

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Identification of Leaf using DWT and SVM Classifier

Identification of Leaf using DWT and SVM Classifier

... pre-processed feature extraction is achieved by applying DWT feature extraction method and also ten shape features of leaves, SVM training algorithm will train the knowledge base ...

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Detection of 2D and 3D Video Transitions Based on EEG Power

Detection of 2D and 3D Video Transitions Based on EEG Power

... Scrutinizing the graphs presented, as expected, the training data show a higher success compared to the test. In general, it is observed that SVM and LDA classifiers are more successful in interpreting graphs than k-NN. ...

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