statistical features
Statistical features ANN recognizer for bivariate process mean shift pattern recognition
... The statistical features-ANN recognizer is useful for implementation in MQC with smaller network size, better ARLs and comparable RA performances compared to the raw data-ANN ...
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Statistical Features and Traditional SA SVM Classification Algorithm for Crack Detection
... sensitive statistical features are extracted from the signals and used as the inputs of Self-Advising Support Vector Machine (SA-SVM) for the classification purpose in civil En- gineering ...
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Automatic Arrhythmia Classification Method Using Simple Statistical Features
... simple statistical features extraction methods and library support vector machine (LIBSVM) ...for features extraction ...the features from them. The features extraction methods that ...
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Information Theoretical and Statistical Features for Intrinsic Plagiarism Detection
... and statistical features includ- ing function word skip n-grams for detect- ing plagiarism ...36 features for clas- sifying plagiarized and non-plagiarized texts in suspicious ...
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Using Statistical Features to Find Phrasal Terms in Text Collections
... uses statistical features of the word n-grams (sequences of n words) found in the documents and a classifier to determine which are valid phrasal ...similar statistical features that might be ...
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Statistical Features-Based Real-Time Detection of Drifted Twitter Spam
... the statistical features of ...the statistical properties of spam tweets vary over time, and thus the performance of existing machine learning based classifiers ...the statistical ...
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Block-based cloud classification with statistical features and distribution of local texture features
... (2010) statistical features such as mean, standard deviation, skewness, and difference are uti- ...textural features including energy, entropy, con- trast, and homogeneity are computed from the ...
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CLASSIFICATION OF MAMMOGRAMS ON ZONE BASED STATISTICAL FEATURES
... wise features are extracted from segmented part of the image which is used to identify the commonly used mammography dataset as normal, benign, or malignant, using nearest neighbor ...
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An investigative study on the influence of correlation of PD statistical features on PD pattern recognition
... φ-q-n statistical parameters and the other comprising the PD φ-q-n statistical parameters plus their correlation ...PD statistical dataset combined with the correlation coefficients appears to show ...
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EPILEPSY DETECTION USING STATISTICAL FEATURES ON EEGSIGNAL
... is a disorder of the central nervous system characterized by loss of consciousness and convulsions. EEG is the recording of electrical activity of the brain signals that can be used to diagnose the epilepsy condition. In ...
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MRI brain scan classification using novel 3 D statistical features
... intensity-based features (IBF), and directional Gabor texture features ...these features were classified by artificial neural network (ANN) after implementing PCA for data ...texture-based ...
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Detection of Cataract by Statistical Features and Classification
... The statistical features as mean, entropy, standard deviation, area, uniformity, intensity were extracted by thresholding ...extracted features were given as input for K-means and ANFIS ...
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Objective extraction and analysis of statistical features of Dansgaard–Oeschger events
... Our analysis suggests that the mechanisms underlying warming and cooling transitions are likely different due to contrasting statistical properties. The stadial duration dis- tribution closely resembles an ...
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File fragment recognition based on content and statistical features
... fragment features, which are obtained from Binary Frequency Distribution (BFD), are reduced by 2 feature reduction algorithms; Sequential Forward Selection algorithm (SFS) as well as Sequential Floating Forward ...
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Dynamics and statistical features of coherent plasma structures in the SOL of a tokamak
... Steep density and temperature gradients are key features of magnetically confined plasma (MCF) in a tokamak configuration. In the presence of a strong confining magnetic field, these gradients lead to a nonlinear ...
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Classification of electroencephalography signal using statistical features and regression classifier
... Brain is a complex organ in human body and it is still a mystery to human being (Eagleman, 2007). Understanding the basic fundamentals of the brain in terms of its physiology and functionality will be the key to solve ...
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Statistical Features Based Image Watermarking Resisting to Geometrical Attacks
... Towards this direction, we use the scaling invariance of shape of an image’s histogram and the property of the histogram to be independent of the pixel position against[r] ...
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Sleep Stages Classification Using Spectral Based Statistical Moments as Features
... EEG features and ...of features for identifying sleep stages with a single EEG channel, leading researchers to modify the feature selection according to the number of classification ...frequency-domain ...
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Extracting Statistical Graph Features for Accurate and Efficient Time Series Classification
... solely statistical features from graphs that are generated from time ...these features are used for building highly accurate clas- sification models using generic classifiers ( ...extract ...
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Facial Expression Recognition by Statistical, Spatial Features and using Decision Tree
... spatial features of the face which provide ...compute statistical features of the face which provide ...both features in order to increase accuracy and classification rate increases to ...
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