Image registration is an important problem in computer vision and has many diverse applications. Registration is the method of aligning two or more images into the same coordinate system to achieve a one-to-one correspondence. While registration of images has been studied in the past, an area that is less explored is nonrigid registration. It turns out that nonrigid registration is very appropr...

The paper presents use of the mini-models method in a classification task. The article briefly describes the method and compares it to the k-nearest neighbor algorithm. The algorithm concentrates only on local query data and uses a data samples only from local neighborhood of the query. The paper presents the results of experiment that compare the effectiveness of mini-models with selected meth...

As special depositional environments which are adjacent to the seas, deltas have provided a field for human habitat establishment. Geomorphic features of deltas are in constant transformation due to their dynamic features. Constructing dams on rivers can intensify these changes and cause either negative or positive consequences. Minab delta in Hormozgan Province of Iran is a round or crescent-s...

In this paper, human face recognition of still images has been proposed. The proposed system involves five steps: face detection by AdaBoost face detector, region of interest (ROI) extraction, feature extraction using discrete wavelet transform (DWT), dimensionality reduction by employing independent component analysis (ICA) and classification using k-Nearest Neighborhood (k-NN) classifier. Exp...

The present paper introduces an adaptive algorithm for competitive training of a nearest neighbor (NN) classifier when using a very small codebook. The new learning rule is based on the well-known LVQ method, and uses an alternative neighborhood concept to estimate optimal locations of the codebook vectors. Experiments over synthetic and real databases suggest the advantages of the learning tec...

A major issue in k-nearest neighbor classification is how to choose the optimum value of the neighborhood parameter k. Popular cross-validation techniques often fail to guide us well in selecting kmainly due to the presence ofmultipleminimizers of the estimatedmisclassification rate. This article investigates a Bayesian method in this connection, which solves the problem of multiple optimizers....

We consider a ring of identical neurons with delayed nearest neighborhood inhibitory interaction. Under general conditions, such a network has a slowly oscillatory synchronous periodic solution which is completely characterized by a scalar delay differential equation with negative feedback. Despite the fact that the slowly oscillatory periodic solution of the scalar equation is stable, we show ...

The patents cover almost all the latest, the most active innovative technical information in technical fields, therefore patent classification has great application value in the patent research domain. This paper presents a KNN text categorization method based on shared nearest neighbor, effectively combining the BM25 similarity calculation method and the Neighborhood Information of samples. Th...

Given a locally uniform sample set P of a smooth surface S. We derive upper and lower bounds on the number k of nearest neighbors of a sample point p that have to be chosen from P such that this neighborhood contains all restricted Delaunay neighbors of p. In contrast to the trivial lower bound, the upper bound indicates that a sampling condition that is used in many computational geometry proo...