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In this paper, a new method for face localization in color images, which is based on co-evolutionary systems, is introduced. The proposed method uses a co-evolutionary system to locate the eyes in a face image. The used coevolutionary system involves two genetic algorithm models. The first GA model searches for a solution in the given environment, and the second GA model searches for useful genetic...
Paroxysmal Atrial Fibrillation (PAF), a really life threatening disease, is the result of irregular and repeated depolarization of the atria. In this paper, patients with PAF disease and their different episodes can be detected by extracting statistical and morphological features from ECG signals and classifying them by applying artificial neural network (ANN), Bayes optimal classifier and K-nearest...
Paroxysmal atrial fibrillation, a really life threatening disease, is the result of irregular and repeated depolarization of the atria. In this paper, an automatic detection and prediction of this critical disease is performed by the use of three groups of features extracted from different parts of ECG signals and classified by KNN, MLP and Bayes optimal classifiers. Finally, the health status of...
According to the literature, many psychiatric phenotypes, brain disorders and/or mental tasks can be detected by analyzing EEG signals. One such a psychiatric phenotype is alcoholism. In this paper the parameters of second order autoregressive model, peak amplitude of the power spectrum, mean of absolute value and the variance of the signal are extracted as features of the signal. The dimension of...
With time-to-market getting the most important issue in system design, reusing the design experiences as well as the IP cores is becoming very critical. Design patterns, intended for simplifying the reuse process, are design experiences that worked well in the past and documented to be reused in the future. In this paper, a design pattern named NnEP (Neural-network-based Embedded systems design Pattern)...
A new method for feature selection based on generic algorithm and its application in face recognition is proposed. Simulation results show the superior performance of the proposed algorithm over the eigenface original method. In comparison to evolutionary pursuit method, the proposed method has a faster training phase and the ability of finding and searching more features using our novel fitness function
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