feature-vector based analysis
FACE RECOGNITION USING DIFFERENT TECHNIQUES A REVIEW
... template based face detection and recognition system that uses a matching pursuit filter to obtain the face vector ...Component Analysis) and LDA(Linear Discriminant Analysis) based ...
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Bayesian texture classification and retrieval based on multiscale feature vector
... multiscale feature vector extracted from a query images is used together with simple distance measure to perform the final ...multiscale feature vector for each texture image which consists of ...
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Automatic Object-Oriented, Spectral-Spatial Feature Extraction Driven by Tobler’s First Law of Geography for Very High Resolution Aerial Imagery Classification
... spatial-spectral feature extraction is a popular strategy for ...that feature extraction is usually time-consuming and depends excessively on ...spatial feature extraction approach based on ...
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Support Vector Machine Ensemble Based on Feature and Hyperparameter Variation.
... global feature vector G to describe many relevant aspects of the current motor pump ...the feature extraction stage and fur- ther use feature selection and ensemble construction to prioritize ...
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Fuzzy Particle Swarm Optimization Based Feature Learning Vector
... cluster analysis, some of the features of a given data set may fall in higher relevance than ...issue, Feature-Weighted Fuzzy C-Means (FWFCM) approaches are helpful in recent ...a feature-weight ...
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A Survey of Machine Learning Based Approaches for Parkinson Disease Prediction
... support vector machines (SVM) based approaches predict to dataset composed of a range of biomedical voice measurements from 31 people, 23 people with Parkinson ...FKNN based system using a 10- fold ...
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Bleeding Detection in Wireless Capsule Endoscope Based on Color Feature Vector
... Color feature is important for bleeding ...color feature extraction, because CIELAB and CMYK represent the color with an intuitive ...color feature from A channel of the CIELAB color space and M ...
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Density-Based Multi Feature Background Subtraction with Support Vector Machine
... Video surveillance systems have long been in use to monitor security sensitive areas. The making of video surveillance systems “smart” requires fast, reliable and robust algorithms for moving object detection, ...
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Consistent performance measurement of a system to detect masses in mammograms based on blind feature extraction
... system based on blind feature extraction by Independent Component Analysis (ICA) and Neural Network (NN) and Support Vector Machine (SVM) classifiers to detect and classify masses in the ...
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A Trust And Energy-Based Efficient Routing Scheme Using Kuder-Richardson Reliability Coefficient For Manets
... multidimensional feature vector called mean vector, which incorporates the number of RREQ messages sent and the number of RREQ received through which average difference in the destination sequence ...
5
To Prepare a Forecasting Proxy Server to Improve Hits Using SVM.
... support vector machine to build up the optimal classification brings difficulties, in [16] Jing Tang ...diagnosis based on principal components analysis and support vector machine is presented ...
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An NN Based Feature Analysis Model for Sleep ...
... signal, feature based analysis is applied over the ...such feature extraction method is QRS complex ...of feature vector under quantitative measures. The feature level ...
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A novel hybrid of genetic algorithm and ANN for developing a high efficient method for vocal fold pathology diagnosis
... initial feature vector based on the combination of the wavelet packet decomposition (WPD) and the Mel frequency cepstral coefficients (MFCCs) is ...initial feature vector, a genetic ...
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Bimodal Biometric Recognition Using PCA
... magnitude feature extraction is done. Feature level fusion is used to get a feature vector for further ...discriminant analysis and linear ...and analysis is ...system. ...
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Unsupervised content classification based non-rigid registration of differently stained histology images.
... MI based registration generally takes a significantly longer time than our method and has larger variance between the different image pairs from the same ...criteria based on ...
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Multi-Label Learning with Class-Based Features Using Extended Centroid-Based Classification Technique (CCBF)
... class-indexing-based term-weighting approach, in which the inverse class frequency (ICF) is incorporated to generate more informative terms. Vale 14 proposed a class-based feature selection method. ...
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Pre-processing Techniques in Sentiment Analysis through FRN: A Review
... sentiment analysis that comprises of three key ...is feature selection and here we analyze it in some ...different feature weighting methods (FF, TF-IDF and ...each feature for every document ...
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A Content based CT Image Retrieval by Advance Multiple Comparison Technique
... the feature vectors are extracted ...the feature vector of the query ...extracted feature vector is compared to the feature vectors stored in the ...the feature of the ...
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Survey paper on Aves Vocalization Detecting System Using Machine Learning
... representation based audio hashing framework for bird species ...archetypal analysis, a matrix factorization technique, to obtain convex-sparse representations of a bird ...
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biometrics, palm print, principal lines, verification
... obtained based on ERR criteria since both FAR and FRR must be as low as possible for the biometric system to work ...shape feature with palm print ...angle feature along with the previous two ...
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