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Evalutation of performance of KNN, MLP and RBF classifiers in emotion detection problem
Emotion Detection has gained increasing attention and become an active research area. The problem is solved with improved feature set with different number of feature groups, by employing different classifiers in order to ...
Determining efficiency of speech feature groups in emotion detection
Features, extract from speech parameter are frequently used in emotion detection problem. Prosodic, MFCC, LPC and band energy feature groups are commonly used in literature to detect emotion in speech. The aim of the study ...
The Effect of Genetic Algorithm Parameters on the Solution of Plate Location Detection
In this study, a new method based on genetic algorithm and neural networks for determining licence plate location is proposed. The effect of genetic algorithm parameters on the quality of solutions is investigated. The ...
On the comparison of classifiers' performance in emotion classification: Critiques and Suggestions
In literature there is a huge body of references available which compare various classifiers in a particular application. However, the reliability of such a comparison is only valid if the model parameters, performance ...
New frameworks to boost feature selection algorithms in emotion detection for improved human-computer interaction
(SPRINGER-VERLAG BERLIN, 2007)
One of the primary aims in human-computer interaction research is to develop an ability to recognize affective state of the user. Such ability is indispensable to have a more human-like nature in human-computer interaction. ...
Implementation of HOG algorithm for Real Time Object Recognition Applications on FPGA based Embedded System
Recent years HOG algorithm has been used to recognize objects in images, with complex content, with a very high success rate. Hardware implementation of this algorithm is very important because of the fact that it can be ...