Efficient content-based similarity search in large multimedia databases requires efficient query processing algorithms for many practical applications. Especially in high-dimensional spaces, the huge number of features is a challenge to existing indexing structures. Due to increasing overlap with growing dimensionality, they eventually fail to deliver runtime improvements. In this work, we prop...

Binary Hashing is widely used for effective approximate nearest neighbors search. Even though various binary hashing methods have been proposed, very few methods are feasible for extremely high-dimensional features often used in visual tasks today. We propose a novel highly sparse linear hashing method based on pairwise rotations. The encoding cost of the proposed algorithm is O(n logn) for n-d...

We consider a clustering problem where we observe feature vectors Xi ∈ R, i = 1, 2, . . . , n, from K possible classes. The class labels are unknown and the main interest is to estimate them. We are primarily interested in the modern regime of p n, where classical clustering methods face challenges. We propose Influential Features PCA (IF-PCA) as a new clustering procedure. In IF-PCA, we select...

Most image or video search engines operate by extracting and storing feature vectors from the multimedia objects. These feature vectors may, for example, consist of colour or texture histograms and can vary considerably in size, say from a few ten numbers to 50,000 numbers. When an image database is queried with a particular example image ("show me similar images"), the corresponding feature ve...

We consider a clustering problem where we observe feature vectors Xi ∈ R, i = 1, 2, . . . , n, from K possible classes. The class labels are unknown and the main interest is to estimate them. We are primarily interested in the modern regime of p n, where classical clustering methods face challenges. We propose Important Features PCA (IF-PCA) as a new clustering procedure. In IFPCA, we select a ...

In this paper, a method for automatic stitching of radiology images based on pixel features has been presented. In this method, according to the smooth texture of radiological images and in order to increase the number of the extracted features after quality enhancement of initial radiology images, 45 degree isotropic mask is applied to each radiology image to observe the image details. After t...

This paper presents the complete algorithm of site response analysis of nonhomogeneous topographic structures using transient two-dimensional boundary element method (BEM). Seismic behaviour of various topographic features including canyon, half plane, sedimentary filled valley and ridge sections, subjected to incident SV and P waves are analysed. The analysis shows the efficiency of the propos...

In this work, a hierarchical ensemble of projected clustering algorithm for high-dimensional data is proposed. The basic concept of the algorithm is based on the active learning method (ALM) which is a fuzzy learning scheme, inspired by some behavioral features of human brain functionality. High-dimensional unsupervised active learning method (HUALM) is a clustering algorithm which blurs the da...

in this paper we have discussed the main features of a finite clement program which we have developed for nonlinear dynamic analysis of plates and shells with material and geometric nonlinear behaviour. for this purpose, initially, the finite element model which we have used is briefly described. afterwards, the nonlinear viscoplastic material model in one-dimensional and multi-dimensional medi...