A novel and powerful perspective on image reconstruction and restoration is to regard the computational objective as the classification of corrupt (= unclassified) pixels using the classification of the nearest uncorrupt (classified) pixels. In Nnearest neighbour (NNN) restoration, the distance transform is used to determine the set of N-or-more classified pixels which are as close, or closer, ...

A new solution method to the Nearest Neighbour Problem is presented. The method is based upon the triangle inequality and works well for small point sets, where traditional solutions are particularly ineffective. Its performance is characterized experimentally and compared with k-d tree and Elias approaches. A hybrid approach is proposed wherein the triangle inequality method is applied to the ...

There is a significant research effort on efficient computing of similarities between objects of non traditional data types as strings, documents, sound tracks or pictures. It is reasonable to use the results of these efforts in the problem of XML tree matching, too. As an XML document has a tree structure and the trees can be transformed into a linear structure, a tree can be regarded as a spe...

We here compare the performance (predictive accuracy and processing time) of different neural network ensembles with that of nearest neighbor classifier ensembles. Concerning the connectionist models, the multilayer perceptron and the modular neural network are employed. Experiments on several real-problem data sets demonstrate a certain superiority of the nearest-neighborbased schemes, in term...

Abstract We study the structure of stationary patterns in bistable lattice dynamical systems posed on rings with a symmetric coupling regime small strength. show that sparse (for instance, nearest-neighbour or next-nearest-neighbour coupling) and all-to-all lead to significantly different solution branches. In particular, leads snaking branches many saddle-node bifurcations, while six saddle no...

The main aim of this paper is to analyse the performance customer behaviour in online shopping by using precision value.A novel Self-organizing map with sample size 10 and k nearest neighbour was iterated at different times for predicting accuracy percentage behaviour. minimum power analysis fixed as 0.8 maximum accepted error 0.5. result proved that got significant results 96% compared K Neare...

This paper reports a comparison study of 5 selected techniques for learning-based pattern classification. The techniques are the Linear Discriminant, the k-Nearest Neighbour Rule, the Classification Tree, and the 2 types of feed-forward artificial neural networks called the Backpropagation network and the Cascade-Correlation network. Each technique is briefly introduced and a test case involvin...

The ultrasonic inspection technique can be very useful to determine the state of non reachable structure. In this paper a method based on the neural network classification to evaluate the corrosion level of non accessible pipes is shown. A set of optimal features constitutes the database and feeds the neural network. These features are chosen by time and frequency features extracted from simula...