feature-based recognition algorithms
Performance Metrics for Eigen and Fisher Feature Based Face Recognition Algorithms
... Face recognition methods mainly deal with images which are of large ...of recognition very ...for feature extraction whereas LDA is used for ...kernel based algorithms are ...
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Face Recognition by Additive Block based Feature Extraction
... Face cognizance technology analyze the particular shape, sample and positioning of the facial aspects. Face consciousness is an extraordinarily intricate technology and is basically software situated. This Biometric ...
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Naive Bayes Classification Based Facial Expression Recognition With Kernel PCA Features
... motion recognition system is classified into3steps: face location determination, feature extraction and emotion ...the feature locations. From the feature points extracted, distances among the ...
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The ICA Based Soft-Computing Algorithms for Signal Cleaning and Feature Selection in (for) Automated ECG Pattern Recognition
... pattern recognition is ...pattern recognition, with the hypothesis that components of an ECG signal generated by different parts of the heart during normal and arrhythmic cardiac cycles might be ...
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REVIEW OF SPEECH AND SPEECH RECOGNITION SYSTEM USING FEATURE EXTRACTION ALGORITHM AND OPTIMIZATION ALGORITHMS
... SVM was developed by Vapnik in 1998 and it is a new class of learning machine which use support vectors and kernels for learning. The kernel machines provide a framework which can be adapted to different tasks and ...
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Discriminant analysis based feature extraction for pattern recognition
... In this set of experiments, the performance of the proposed kernelized algorithm, the Algorithm KC, and that of three other kernelized algorithms, the MGSVD-KDA, KRDA and KPCA+LDA algo[r] ...
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Robust RGB-D face recognition using attribute-aware loss
... (CNN) based face recognition algorithms typically learn a discriminative feature mapping, using a loss function that enforces separation of features from different classes and/or aggregation ...
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Layered Feature Recognition Algorithm Based on Combined Convolution
... Many algorithms are pursuing sparse property, because the property has the following two advantages: firstly, it has the property of automatic feature selection; lastly, it makes the model easier to ...
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Iris feature extraction and recognition based on different transforms
... features based on 2-D Fast Discrete Curvelet Transform (FDCT) is ...anisotropic feature vector for each sub-image is derived using the directional energies of the curvelet ...six feature vectors are ...
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Performance Analysis of Classification Algorithms for Activity Recognition using Micro-Doppler Feature
... Micro-Doppler signatures uniquely represent the distinctive features generated from the relative motion of structural components of an object/body. A brief history of micro-Doppler and relevant source material are ...
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Facial Feature Extraction Based On FPD and GLCM Algorithms
... ear based biometric ...face recognition using adaboost improved fast PCA ...face recognition methods for Eigen faces which are based on the PCA technique for face ...facial feature ...
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Index-Term:- Spectral features, spectral density feature selection, pattern recognition, retrieval accuracy.
... pattern recognition is now emerging at a very rapid rate, with its applications, been diversified from basic school level learning to high precision applications, such as medical applications, military ...
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Multi-Algorithmic Face Authentication System
... face recognition architecture which uses three different feature extraction algorithms to address the problems of illumination, pose variant and incorporates sensor fusion for handling occlusion ...
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Image Segmentation Based Face Recognition Using Enhanced SPCA-KNN Method
... in algorithms implementation ...constant feature (or descriptor) within the image. SIFT (Scale-invariant feature transform) options are well-tried to be sturdy against face look variability so ...
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Algorithms for Hardware Based Pattern Recognition
... in feature extraction and ...for feature extraction, pattern recognition, and classification ...method based on the power spectrum of the Fourier Trans- form, or on several other ...
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Comparison Of Different Face Recognition Algorithms
... are based on some feature means they don’t exactly know the correct face but they know the feature of the particular face of the person ...special feature by which exact person is recognize, ...
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Improving of Feature Selection in Speech Emotion Recognition Based-on Hybrid Evolutionary Algorithms
... extracted feature from spectral information are Mel Frequency Cepstral Coefficients that represent the short-term power spectrum of a frame speech using the linear cosine transform of a log power spectrum on a ...
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PROSODIC FEATURE BASED TEXT DEPENDENT SPEAKER RECOGNITION USING MACHINE LEARNING ALGORITHMS
... speech recognition system using MLP and ...MLP’s recognition accuracies are better than ...learning algorithms namely MLP, RBFN, ...ML algorithms outperform all other ML algorithms in ...
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Title: Finger Vein Recognition Using Haar Wavelet Transform
... Many algorithms were proposed and implemented to recognize finger vein, [4] discussed an approach of finger vein recognition by combining local feature based on a Local Binary Pattern (LBP) ...
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A Survey on Local Feature Based Face Recognition Methods
... To improve the FR performance both Gabor wavelet and LBP are combined.GV-LBP-TOP is one such method in which information are obtained by assembling scale, orientation and spatial domain to form third order volume. This ...
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