The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper presents a novel method for facial expression classification that employs the combination of two different feature sets in an ensemble approach. A pool of base classifiers is created using two feature sets: Gabor filters and local binary patterns (LBP). Then a multi-objective genetic algorithm is used to search for the best ensemble using as objective functions the accuracy and the size...
Recognizing faces with altered appearances is a challenging task and is only now beginning to be addressed by researchers. The paper presents an evolutionary granular approach for matching face images that have been altered by plastic surgery procedures. The algorithm extracts discriminating information from non-disjoint face granules obtained at different levels of granularity. At the first level...
This paper presents an efficient algorithm for matching sketches with digital face images. The algorithm extracts discriminating information present in local facial regions at different levels of granularity. Both sketches and digital images are decomposed into multi-resolution pyramid to conserve high frequency information which forms the discriminating facial patterns. Extended uniform circular...
Recently, an evolutionary algorithm named Genetic Network Programming with Estimation of Distribution Algorithm (GNP-EDA) has been proposed and applied to extract classification rules for solving traffic prediction problems. The measures such as the support, confidence and χ2 value are adopted to evaluate the interestingness of a large number of rules extracted from traffic databases in the above...
One of the most important issues in any association rule mining is the interpretation and evaluation of discovered rules. Thus, most algorithms employ the support-confidence framework for evaluating association and classification rules. Unfortunately, recent studies show that the support and confidence measures are insufficient for filtering out uninteresting association rules, for instance, even...
In this paper, a class association rule mining approach based on Genetic Network Programming (GNP) for detecting network intrusion combining misuse detection and anomaly detection is proposed. The proposed approach is an extension of the intrusion detection approach using GNP, so it can detect and distinguish normal, known intrusion and unknown intrusion. The simulation result shows that the detection...
When data objects that are the subject of analysis using machine learning techniques are described by a large number of feature (i.e. the data is high dimension) it is often beneficial to reduce the dimension of the data. dimensionality reduction (DR) can be beneficial not only reasons of computational efficiency but also because it can improve the accuracy of the analysis. Now we have tried to introduce...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.