introduction: raman spectroscopy, that is a spectroscopic technique based on inelastic scattering of monochromatic light, can provide valuable information about molecular vibrations, so using this technique we can study molecular changes in a sample. material and methods: in this research, 153 raman spectra obtained from normal and dried skin samples. baseline and electrical noise were eliminat...

manual fingerprint classification algorithms are very time consuming, and usually not accurate. fast and accurate fingerprint classification is essential to each afis (automatic fingerprint identification system). this paper investigates a fingerprint classification algorithm that reduces the complexity and costs associated with the fingerprint identification procedure. a new structural algorit...

Manual fingerprint classification algorithms are very time consuming, and usually not accurate. Fast and accurate fingerprint classification is essential to each AFIS (Automatic Fingerprint Identification System). This paper investigates a fingerprint classification algorithm that reduces the complexity and costs associated with the fingerprint identification procedure. A new structural algorit...

Manual fingerprint classification algorithms are very time consuming, and usually not accurate. Fast and accurate fingerprint classification is essential to each AFIS (Automatic Fingerprint Identification System). This paper investigates a fingerprint classification algorithm that reduces the complexity and costs associated with the fingerprint identification procedure. A new structural algorit...

in this paper, an unsupervised classification method using spatial contextual information for polarimetric sar (polsar) image classification is proposed. first, an unsupervised classification based on 2d h/▁α plane was performed, using cloude/pottier target decomposition algorithm. in order to compute the initial values of the cluster centers and hence a rapid convergence of the algorithm, the ...

with the explosive growth in amount of information, it is highly required to utilize tools and methods in order to search, filter and manage resources. one of the major problems in text classification relates to the high dimensional feature spaces. therefore, the main goal of text classification is to reduce the dimensionality of features space. there are many feature selection methods. however...

due to the complex physical properties of the detected targets using sonar systems, identification and classification of the actual targets is among the most difficult and complex issues of this field. considering the characteristics of the detected targets and unique capabilities of the intelligent methods in classification of their dataset, these methods seem to be the proper choice for the t...

since it is essential to deliver smoothed sinusoidal voltage to the customers, diagnosing power quality (pq) events has played important role in power delivery and conversion. this diagnostic scheme should be accurate to classify pq events from other events in power system. also it should be fast enough to rapidly mitigate pq events. in this paper, an algorithm based on core vector machine (cvm...

microarray data have an important role in identification and classification of the cancer tissues. having a few samples of microarrays in cancer researches is always one of the most concerns which lead to some problems in designing the classifiers. for this matter, preprocessing gene selection techniques should be utilized before classification to remove the noninformative genes from the microa...

One of the important issues in speech emotion recognizing is selecting of appropriate feature sets in order to improve the detection rate and classification accuracy. In last studies researchers tried to select the appropriate features for classification by using the selecting and reducing the space of features methods, such as the Fisher and PCA. In this research, a hybrid evolutionary algorit...