Wavelet transformation

Segmentation of partially-blurred images using wavelet transform

In the research a method for segmentation of partially-blurred images using the wavelet transformation, particularly coiflet of the order L=3 is presented. The entropy is used as a segmentation criterion based on wallet transformation. K-means method is used for image segmentation. Developed method was tested and has shown good results of his work; it correctly performs more than 82 % of pixels of image, and in many individual cases, more than 90 %.

Hybrid swarm negative selection algorithm for dna-microarray data classification

In the paper, a classification method is proposed. It is based on Combined Swarm Negative Selection Algorithm, which was originally designed for binary classification problems. The accuracy of developed algorithm was tested in an experimental way with the use of microarray data sets. The experiments confirmed that direction of changes introduced in developed algorithm improves its accuracy in comparison to other classification algorithms.