Texture analysis has been very much used in medical image problems as well as related areas such as computer vision and pattern recognition. Among all medical image task detection of microcalcification on mammograms is the most difficult one because breast cancer is the most prevalent cancer that leads to death in women today. More over microcalcification are deposits of calcium that can be see...

The distinction between supervised and unsupervised categorization has had a profound influence in related research. We consider a mechanism, attentional selection, possibly shared by models of supervised and unsupervised categorization. In supervised models such as the Generalized Context Model (GCM; Nosofsky, 1988), attentional selection emphasizes dimensions which are relevant for a taught c...

Classification methods can be divided into supervised and unsupervised methods. The supervised classifier requires a training set for the classifier parameter estimation. In the case of absence of a training set, the popular classifiers (e.g. K-Nearest Neighbors) can not be used. The clustering methods are considered as unsupervised classification methods. This paper presents an idea of the uns...

Seismic facies analysis (SFA) aims to classify similar seismic traces based on amplitude, phase, frequency, and other seismic attributes. SFA has proven useful in interpreting seismic data, allowing significant information on subsurface geological structures to be extracted. While facies analysis has been widely investigated through unsupervised-classification-based studies, there are few cases...

To satisfy the robust requirement when designing fault identifying method, this paper proposes a novel method to identify sensor fault. Conventional fault identifying method could only classify fault into explicit set. Yet, when a novel faulty pattern occurs, the conventional method can not identify this new pattern and will classify it into a set known ahead of time. For the purpose of robustn...

This paper describes the time variant changes in satellite images using Self Organizing Feature Map (SOFM) technique associated with Artificial Neural Network. In this paper, we take a satellite image and find the time variant changes using above technique with the help of MATLAB. This paper reviews remotely sensed data analysis with neural networks. First, we present an overview of the main co...

Unlike many black-box algorithms in machine learning, prototype based models offer an intuitive interface to given data sets since prototypes can directly be inspected by experts in the field. Most techniques rely on Euclidean vectors such that their suitability for complex scenarios is limited. Recently, several unsupervised approaches have successfully been extended to general possibly non-Eu...

This paper compares multilook Polarimetric SAR (PolSAR) image classification using three types of learning: a supervised, an unsupervised and a semisupervised. The multilook PolSAR pixel values are complex covariance matrices and they are described by mixtures of Wishart distributions. Tests in synthetic and real images showed that the supervised and semisupervised classifications provided the ...