Since most common form of cervical cancer starts with pre-cancerous changes, a flawless detection of these changes becomes an important issue to prevent and treat the cervix cancer. There are 2 ways to stop this disease from developing. One way is to find and treat pre-cancers before they become true cancers, and the other is to prevent the pre-cancers in the first place. The presented approach...

This paper is concerned with the development of a novel classifier for automatic mass detection of mammograms, based on contourlet feature extraction in conjunction with statistical and fuzzy classifiers. In this method, mammograms are segmented into regions of interest (ROI) in order to extract features including geometrical and contourlet coefficients. The extracted features benefit from...

This paper encompasses an outline that hardens the distinctive executions and proposals of Intrusion Detection. NB is one of the classification methods applied in intrusion detection system which is an effective probabilistic classifier employing the Bayes’ theorem with naive feature independence assumptions. Each data transmitted is captured and analyzed for malicious content, reveal the layer...

In this letter we propose a piece-wise linear (PL) classifier for use as the decision stage in a two-modal verification system, comprised of a face and a speech expert. The classifier utilizes a fixed decision boundary that has been specifically designed to account for the effects of noisy audio conditions. Experimental results on the VidTIMIT database show that in clean conditions, the propose...

Although addressed in many papers, classifier dependency is still not well defined. Continuously being described by variety of statistical models from conditional probability to diversity measures, dependency among classifier outputs was recently shown to have a crucial impact on the performance of multiple classifier system. However, individual classifier performances still represent competiti...

Given their escalating number and variety, combating malware is becoming increasingly strenuous. Machine learning techniques are often used in the literature to automatically discover models patterns behind such challenges create solutions that can maintain rapid pace at which evolves. This article compares various tree-based ensemble methods have been proposed analysis of PE malware. A an unco...