This paper discusses the capability of the complex Wishart classifier for sea ice and classification using multifrequency, fully polarimetric SAR data. C-, L-, and P-band data acquired by the JPL AIRSAR in the Beaufort sea was used. Classification using the unsupervised Wishart classifier is a twostage process. An initial classification is required to seed the algorithm and can be derived using...

This paper experimentally compares the performance of discriminative and generative classifiers for cost sensitive learning. There is some evidence that learning a discriminative classifier is more effective for a traditional classification task. This paper explores the advantages, and disadvantages, of using a generative classifier when the misclassification costs, and class frequencies, are n...

This paper proposes a two-step method for Chinese text categorization (TC). In the first step, a Naïve Bayesian classifier is used to fix the fuzzy area between two categories, and, in the second step, the classifier with more subtle and powerful features is used to deal with documents in the fuzzy area, which are thought of being unreliable in the first step. The preliminary experiment validat...

The goal of this study was to examine the possibility of training machine learning algorithms to differentiate between the performance of good notes and bad notes. Four trumpet players recorded a total of 239 notes from which audio features were extracted. The notes were subjectively graded by five brass players. The resulting dataset was used to train support vector machines with different gro...

This paper propose two decision fusion-based multitemporal classifiers, namely, the jointly likelihood and the weighted majority fusion classifiers, that are derived using two different definitions of the minimum expected cost. Without any overhead incurred by multitemporal processing, a user-selected conventional pixelwise classifier makes local class decisions separately using each temporal d...

A new class of plug in classification techniques have recently been developed in the statistics and machine learning literature. A plug in classification technique (PaCT) is a method that takes a standard classifier (such as LDA or TREES) and plugs it into an algorithm to produce a new classifier. The standard classifier is known as the Plug in Classifier (PiC). These methods often produce larg...

ultrasound imaging is a popular and noninvasive tool frequently used in the diagnoses of liver diseases. a system to characterize normal,fatty and heterogeneous liver, using textural analysis of liver ultrasound images, is proposed in this paper. the proposed approach isable to select the optimum regions of interest of the liver images. these optimum regions of interests are analyzed by two lev...

An evidence theoretic classification method is proposed in this paper. In order to classify a pattern we consider its neighbours, which are taken as parts of a single source of evidence to support the class membership of the pattern. A single mass function or basic belief assignment is then derived, and the belief function and the pignistic (“betting rates”) probability function can be calculat...

Sensor drift is the most challenging problem in gas sensing at present. We propose a novel two-dimensional classifier ensemble strategy to solve the gas discrimination problem, regardless of the gas concentration, with high accuracy over extended periods of time. This strategy is appropriate for multi-class classifiers that consist of combinations of pairwise classifiers, such as support vector...

Rapid popularization of smart cell phone equipped with camera has led to a number of new legal and criminal problems related to multimedia such as digital image, which makes cell phone source identification an important branch of digital image forensics. This paper proposes a classifier combination based source identification strategy for cell phone images. To identify the outlier cell phone mo...