Multiple classifier systems combine several individual classifiers to deliver a final classification decision. An increasingly controversial question is whether such systems can outperform the single best classifier and if so, what form of multiple classifier system yields the greatest benefit. In this paper the performance of several multiple classifier systems are evaluated in terms of their ...

An image classification scheme using Naïve Bayes Classifier is proposed in this paper. The proposed Naive Bayes Classifier-based image classifier can be considered as the maximum a posteriori decision rule. The Naïve Bayes Classifier can produce very accurate classification results with a minimum training time when compared to conventional supervised or unsupervised learning algorithms. Compreh...

multi-spectral remotely sensed data is useful information source for the detection of surface changes and change detection is a major application of the remotely sensed data. this study is conducted to investigate capability of sensor liss-iii of irs-p6resource satellite data for providing land cover map, in najm abad of savojbolagh region with 20000 ha area. the images of 26th june, 2006 were ...

introduction breast cancer is the second cause of mortality among women. early detection of it can enhance the chance of survival. screening systems such as mammography cannot perfectly differentiate between patients and healthy individuals. computer-aided diagnosis can help physicians make a more accurate diagnosis. materials and methods regarding the importance of separating normal and abnorm...

Recent work in Bayesian classifiers has shown that a better and more flexible representation of domain knowledge results in better classification accuracy. In previous work [1], we have introduced a new type of Bayesian classifier called Case-Based Bayesian Network (CBBN) classifiers. We have shown that CBBNs can capture finer levels of semantics than possible in traditional Bayesian Networks (...

Robust face alignment is crucial for many face processing applications. As face detection only gives a rough estimation of face region, one important problem is how to align facial shapes starting from this rough estimation, especially on face images with expression and pose changes. We propose a novel method of face alignment by building a hierarchical classifier network, connecting face detec...

This paper proposes a reduct construction method based on discernibility matrix simplification. The method works with genetic algorithm. To identify potential problems and prevent complete failure of bearings, a new method based on rule-based classifier ensemble is presented. Genetic algorithm is used for feature reduction. The generated rules of the reducts are used to build the candidate base...

In this paper, the cooperation of four feature families for handwritten digit recognition using SVM (Support Vector Machine) classifiers is examined. We investigate the advantages and weaknesses of various cooperation schemes based on classifier decision fusion using statistical reasoning. Although most of presented cooperation schemes are variations and adaptations of existing ones, such an ex...

Multiple classifier systems (MCSs) based on the combination of a set of different classifiers are currently used to achieve high pattern-recognition performances [1]. For each pattern, the classification process is performed in parallel by different classifiers and the results are then combined according to some decision “fusion” method (e.g., the majority-voting rule) [1]. The majority of such...

In classifier combining, one tries to fuse the information that is given by a set of base classifiers. In such a process, one of the difficulties is how to deal with the variability between classifiers. Although various measures and many combining rules have been suggested in the past, the problem of constructing optimal combiners is still heavily studied. In this paper, we discuss and illustra...