In present days remote sensing is most used application in many sectors. This remote sensing uses different images like multispectral, hyper spectral or ultra spectral. The remote sensing image classification is one of the significant method to classify image. In this state we classify the maximum likelihood classification with fuzzy logic. In this we experimenting fuzzy logic like spatial, spe...

This paper presents a novel approach to the weak classifier selection based on the GentleBoost framework. We include explicitly the notion of neighborhood in one of the most common weak learner in boosting, the decision stumps. The availability of neighboring points adds a new parameter to the decision stump, the feature set (i.e. neighborhood), and turns the single branch selection of the deci...

The difference of Fuzzy Joint Points (FJP) algorithm from other neighborhood-based clustering algorithms is that it uses the concept of fuzzy neighborhood when computing the neighborhood relations. Among the proposed methods, none of them is perfect for all aspects of clustering requirements. Although FJP algorithm has superiority by its advantages of robustness and optimal determination of the...

The aim of this paper is to introduce and study the fuzzy neighborhood, the limit fuzzy number, the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence on the base which is adopted by Abdul Hameed every real number r is replaced by a fuzzy number r either triangular fuzzy number or singleton fuzzy set fuzzy point . And then, we will consider that some results re...

In this paper, we focus on Global Self-consistent, Hierarchical, High-resolution Geography (GSHHG) database registration for remote sensing images taken from geostationary meteorological satellites. While the accuracy of feature matching is the key component. To improve it, we propose a neighborhood geometry-based feature matching scheme which includes three steps: neighborhood coding, verifica...

We consider some modifications of the neural gas algorithm. First, fuzzy assignments as known from fuzzy c-means and neighborhood cooperativeness as known from self-organizing maps and neural gas are combined to obtain a basic Fuzzy Neural Gas. Further, a kernel variant and a simulated annealing approach are derived. Finally, we introduce a fuzzy extension of the ConnIndex to obtain an evaluati...

the primary objective of the current study is to produce karstification potentiality maps in northeast of khuzestan province, iran, using both fuzzy logic and ahp models as an additional tool in hydrogeological research. geographic information systems (gis) and remote sensing (rs) are used to create two maps depicting the development of the karstification, consisting of five classes, showing th...