Set based recognition (i.e, using a set of instances together for recognition) has been attracting more and more attention in recent years, benefitting from two facts: the difficulty of collecting sets of images for recognition fades quickly, and set based recognition models generally outperform the ones for single instance based recognition. In the past few years various approaches have been p...

Natural images captured in bad weather conditions often suffer from poor visibility. Dehazing, the process of removing haze from a single input image or multiple images, is a crucial task in image and video processing, which is quite challenging because the number of freedoms is lager than the number of observations. In this paper, we propose a novel method to reduce the block artifacts and hal...

Let A be a nonempty closed subset (resp. nonempty bounded closed subset) of a metric space (X, d) and x ∈ X \ A. The nearest point problem (resp. the farthest point problem) w.r.t. x considered here is to find a point a0 ∈ A such that d(x, a0) = inf{d(x, a) : a ∈ A} (resp. d(x, a0) = sup{d(x, a) : a ∈ A}). We study the well posedness of nearest point problems and farthest point problems in geod...

Given n demand points in the plane, the p-center problem is to find p supply points (anywhere in the plane) so as to minimize the maximum distance from a demo& point to its respective nearest supply point. The p-median problem is to minimize the sum of distances from demand points to their respective nearest supply points. We prove that the p-center and the p-media problems relative to both the...

Given n data points in d-dimensional space, nearest-neighbor searching involves determining the nearest of these data points to a given query point. Most averagecase analyses of nearest-neighbor searching algorithms are made under the simplifying assumption that d is fixed and that n is so large relative to d that boundary effects can be ignored. This means that for any query point the statisti...

In this paper we propose an algorithm for answering reverse nearest neighbor (RNN) queries, a problem formulated only recently. This class of queries is strongly related to that of nearest neighbor (NN) queries, although the two are not necessarily complementary. Unlike nearest neighbor queries, RNN queries nd the set of database points that have the query point as the nearest neighbor. There i...

We prove a strong convergence result for a sequence generated by Halpern's type iteration for approximating a common fixed point of a countable family of quasi-Lipschitzian mappings in a real Hilbert space. Consequently, we apply our results to the problem of finding a common fixed point of asymptotically nonexpansive mappings, an equilibrium problem, and a variational inequality problem for co...

A database is populated with a set of points represented by n-tuples of real numbers. A query consists of a point q (not necessarily in the database) and an integer k, asking for the k "nearest" database points to the query point. The exact output for the query consists of the k nearest points, but if the database is large and a quick response is required, a good approximate output is sought. A...

Outlier detection is very important functionality of data mining, it has enormous applications. This paper proposes a clustering based approach for outlier detection using spatio-temporal data. It uses three step approach to detect spatiotemporal outliers. In the first step of outlier detection, clustering is performed on the spatio-temporal dataset with proposed Spatio-Temporal Shared Nearest ...