multiple feature
The on line detection of engine misfire at low speed using multiple feature fusion with fuzzy pattern recognition
... a feature selection process can be performed before the multiple feature fusion procedure described in sec- tion ...the feature vector shown ...
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Face Recognition under Different Lighting Conditions Using Multiple Feature Fusion
... robust feature extraction and multiple feature ...local feature sets.In the proposed method, an additional feature set is extracted using Elongated Multi Block Local Ternary Pattern ...
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Multiple feature use in pigeons’ category discrimination: The influence of stimulus set structure and the salience of stimulus differences
... determination of pigeons’ response to multidimensional stimuli, which essentially rely on associative processes alone. But the present results are not entirely comfortable from the point of view of such theories. ...
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Strong and Agitable Access Control with Multiple Feature Authorities for Public Cloud Storage
... botches have been made or malignant practices have been actualized during the time spent mystery key age and appropriation. For instance, an expert may erroneously disseminate mystery keys past client's honest to ...
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Research on Gesture Recognition Based on Improved GBMR Segmentation and Multiple Feature Fusion
... The initial gesture recognition process mainly use the machinery and typical equipment, such as data gloves, to obtain manual space information. At present, compared with wearable devices, gesture recognition based on ...
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Complementary human detection and multiple feature based tracking using a stereo camera
... Various approaches have been presented for tracking multiple humans. One work [1] integrated soft biomet- rics with an appearance model in a single-camera setting. Generating coarse representation of a target ...
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Advanced Content Based Image Retrieval Using Multiple Feature Extraction
... ABSTRACT:Due to the enormous increase inimage database sizes, as well as its vast deployment in various applications, many Content Based Image Retrieval (CBIR) systems have been developed. The challenge, however, is in ...
8
Dutch and German 3 year olds’ representations of voicing alternations
... Single Feature Hypothesis predicts that mispronunciations of /t/ as *[d] will be noticed, and therefore, predicts differences in looking behaviour to correct pronunciations and mispronunciations in all plural ...
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Region Based Image Retrieval Approach Using SVM with Shape and Texture Based Feature
... combine multiple feature, to get the better performance than the single feature in medical ...The feature such a shape and texture are important role in the proposed ...
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Early Diagnosis of Parkinson’s Disease based on Transcranial Sonography
... L. Chen [5, 6] combined the geometrical moments with statistical moments (mean, variance, entropy, skewness and etc.) and texture features are extracted using a cache of Gabor filter into a set of feature vectors, ...
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A Multimodal Approach to Biometric Recognition
... resolution). Feature level fusion refers to combining different feature vectors that are obtained by either using multiple sensors or employing multiple feature extraction algorithms on ...
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An Accurate Ecg Feature Extraction Method For Detecting Multiple Cardiovascular Diseases
... The P-wave is the first deflection of the ECG. It results from depolarizationof the atria.Atrial repolarisation occurs during ventricular depolarization and is obscured.The QRS complex corresponds to the ventricular ...
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Iterative learning control for image feature extraction with multiple-image blends
... When the input data to an algorithm is too large to be processed and it is suspected to be redundant (e.g., the same measurement in both feet and meters, or the repetitiveness of images presented as pixels), then it can ...
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Fingerprint Feature Extractors Using Multiple Machine Learning: A Comparative In The Study
... the feature extraction process helps us to perform pattern matching process with existing fingerprint images this matching process is based on the Matchscore ...
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A feature selection method based on multiple kernel learning with expression profiles of different types
... most feature selection methods can be divided into three categories: filter methods, wrapper methods, and embedded methods ...of feature selection search and the construction of the clas- sification ...
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Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
... adds each feature into the models of either none or all of the tasks (Obozinski et al., 2009) for the multi-task case and selects either none or all the features from a given group in the case of group sparsity. ...
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Spatio-Temporal Graphical-Model-Based Multiple Facial Feature Tracking
... facial feature tracking is very important in the com- puter vision field: it needs to be carried out before video- based facial expression analysis and expression ...facial feature tracking is also very ...
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A multiple sequential orthogonal least squares algorithm for feature ranking and subset selection
... and feature extraction are two commonly encountered problems in statistical pattern ...instance feature extraction and feature selection in statistical pattern recognition, often involves a group of ...
18
User Authentication Incorporating Feature Level Data Fusion of Multiple Biometric Characteristics
... • Fuzzy Classiers. The result of classication may not always be certain. That is, there may be doubt about the result, or the input pattern could be classied as a member of more than one class. Feature selection ...
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User Authentication Incorporating Feature Level Data Fusion of Multiple Biometric Characteristics
... As the new ngerprint representation method resulted in a standard length feature vector for each ngerprint, data alignment and subsequent feature level data fusion was eciently and practicably facilitated. ...
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