Feature selection is the essential process to obtain the best feature vectors in pattern recognition system. These feature vectors contain information describing the original data’s important characteristics. In this research, a framework based on factor analysis technique namely the Principal Component Analysis (PCA) is performed to determine the best features extracted from the daily load cur...

The challenging issue in microarray technique is to analyze and interpret the large volume of data. This can be achieved by clustering techniques in data mining. In hard clustering like hierarchical and k-means clustering techniques, data is divided into distinct clusters, where each data element belongs to exactly one cluster so that the out come of the clustering may not be correct in many ti...

Brain tumor is most vital disease which commonly penetrates in the human beings. Studies based on brain tumor confirm that people affected by brain tumors die due to their erroneous detection. In this paper, an enhanced Fuzzy CMeans segmentation (FCM) technique is proposed for detecting brain tumor. To justify the performance of the proposed method, a comparative analysis is being carried out w...

Brain tumor is the most deadly disease that affects human life span. To segment the brain tumor part, many segmentation techniques have been emerged in image processing like region based Segmentation, Boundary based segmentation. In this paper, several entropies based methods and several cluster techniques are compared and analyzed for brain tumor segmentation. Several entropies such as rough e...

The problem of lip contour detection is critical in the lipreading systems based on contour processing. The typical contour detection strategy based on image segmentation in homogeneous regions fails in the case when the mouth images available for lipreading are lowcontrast gray level images. Most of the solutions adopted require manual marking of some contour points. Here we propose a new solu...

The need and importance of automatically recognizing emotions from human speech has grown with the increasing role of human-computer interaction applications. This paper explores the detection of domain-specific emotions using a fuzzy inference system to detect two emotion categories, negative and nonnegative emotions. The input features are a combination of segmental and suprasegmental acousti...

The fuzzy time series approaches, which recently are intensively considered by the researchers, consist of three stages of fuzzification, determination of fuzzy relations and defuzzification. Several studies using different approaches in these steps have been conducted in literature. In most of the studies related fuzzy time series, the membership degrees of belonging to every fuzzy set of each...

An electronic nose (EN) is an artificial olfactory system that tries to perform the same task as human olfactory system and widely used in the gas analysis field. EN consists of an array of chemical sensors possessing broad specificity, coupled to electronics and software that allow feature extraction – extraction of salient data for further analysis, together with pattern recognition – identif...

Clustering for data aggregation is essential nowadays for increasing the wireless sensor network (WSN) lifetime, by collecting the monitored information within a cluster at a cluster head. The clustering algorithm reduces overall transmission of data from each sensor to the sink node thus energy spent by individual sensor node is minimized .The cluster heads collect all sensed information from ...

P. Scheunders Vision Lab, Dept. of Physics, RUCA University of Antwerp, Groenenborgerlaan 171, 2020 Antwerpen, Belgium email: [email protected] Abstract: In this paper color image quantization by clustering is discussed. A clustering scheme, based on competitive learning is constructed and compared to the well-known C-means clustering algorithm. It is demonstrated that both perform equally w...