The proposed method is to recognize objects based on application of Local Steering Kernels (LSK) as Descriptors to the image patches. In order to represent the local properties of the images, patch is to be extracted where the variations occur in an image. To find the interest point, Wavelet based Salient Point detector is used. Local Steering Kernel is then applied to the resultant pixels, in ...

Many current local search algorithms for SAT fall into one of two classes. Random walk algorithms such as Walksat/SKC, Novelty+ and HWSAT are very successful but can be trapped for long periods in deep local minima. Clause weighting algorithms such as DLM, GLS, ESG and SAPS are good at escaping local minima but require expensive smoothing phases in which all weights are updated. We show that Wa...

We consider an abstract second order linear equation with a strong dissipation, namely a friction term which depends on a power of the “elastic” operator. In the homogeneous case, we investigate the phase spaces in which the initial value problem gives rise to a semigroup, and the further regularity of solutions. In the nonhomogeneous case, we study how the regularity of solutions depends on th...

This paper describes a novel approach based on fuzzy logic technique for smoothing process on the unstructured meshes in 2D. The proposed method works local on triangulation. Therefore, remeshing does not require. It is known that other smoothing operations such as laplacian smoothing , optimization based smoothing, angle based smoothing, and hybrid smoothing operations work global. That is, in...

In this paper, we propose a continuation method for box constrained variational inequality problems. The continuation method is based on the class of Gabriel-Mor e smooth functions and has the following attractive features: It can start from any point; It has a simple and natural neighborhood deenition; It solves only one approximate Newton equation at each iteration; It converges globally line...