Browsing by Subject "Number theory"
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Item Open Access Çarpıcıdan bağımsız ortak fark matrisi kullanarak video ve görüntü işleme(IEEE, 2009-04) Çetin, A. Enis; Duman, Kaan; Tuna, Hakan; Eryıldırım, AbdulkadirBu bildiride gerçel sayılar üzerinde yarı grup kuran yeni bir iletmen tanımlayarak elde edilen bir bölge betimleyicisi ile hareketli obje takibi, yüz sezimi, plaka bulma, bölge betimleme için kullanılabilecek hızlı bir algoritma sunuyoruz. Bu yeni iletmen hiçbir çarpma gerektirmez. Bu iletmeni kullanarak, imge bölgelerini nitelendiren ve ortak fark adı verilen bir matris tanımlıyoruz. Plaka bulma uygulamasında ortak fark matrislerinı plaka bölgelerinden kestirip, bunları bir veritabanında saklıyoruz. Plaka bölgelerini gerçek zamanlı videoda tanımlamak için ilk önce videodaki hareketli bölgeleri taşıyan imgeleri belirliyoruz, sonra hareketli bölgelerin içinde ya da bütün resim içinde plaka büyüklüğündeki bölgelerin ortak ayrık matrislerini veritabanındaki plaka ortak ayrık matrisleriyle karşılaştırarak bölge içinde plaka olup olmadığını belirliyoruz.Item Open Access Comparison of the formulations for a hub-and-spoke network design problem under congestion(Elsevier, 2016) Kian, Ramer; Kargar, KamyarIn this paper, we study the hub location problem with a power-law congestion cost and propose an exact solution approach. We formulate this problem in a conic quadratic form and use a strengthening method which rests on valid inequalities of perspective cuts in mixed integer nonlinear programming. In a numerical study, we compare two well known types of mathematical modeling in the hub-location problems which are solved with different branch and cut strategies. The strength and weakness of the formulations are summarized based on an extensive numerical study over the CAB data set. © 2016 Elsevier LtdItem Open Access Condition number in recovery of signals from partial fractional fourier domain information(Optical Society of America, 2013-06) Oktem F. S.; Özaktaş, Haldun M.The problem of estimating unknown signal samples from partial measurements in fractional Fourier domains arises in wave propagation. By using the condition number of the inverse problem as a measure of redundant information, we analyze the effect of the number of known samples and their distributions.Item Open Access On a conjecture of Ilmonen, Haukkanen and Merikoski concerning the smallest eigenvalues of certain GCD related matrices(Elsevier Inc., 2016) Altinişik, E.; Keskin, A.; Yildiz, M.; Demirbüken, M.Let Kn be the set of all n×n lower triangular (0,1)-matrices with each diagonal element equal to 1, Ln={YYT:Y ∈ Kn} and let cn be the minimum of the smallest eigenvalue of YYT as Y goes through Kn. The Ilmonen-Haukkanen-Merikoski conjecture (the IHM conjecture) states that cn is equal to the smallest eigenvalue of Y0Y0 T, where Y0 ∈ Kn with (Y0)ij = (Formula presented.) for i > j. In this paper, we present a proof of this conjecture. In our proof we use an inequality for spectral radii of nonnegative matrices. © 2015 Elsevier Inc.Item Open Access Shadow detection using 2D cepstrum(SPIE, 2009-04) Töreyin, B. Uğur; Çetin, A. EnisShadows constitute a problem in many moving object detection and tracking algorithms in video. Usually, moving shadow regions lead to larger regions for detected objects. Shadow pixels have almost the same chromaticity as the original background pixels but they only have lower brightness values. Shadow regions usually retain the underlying texture, surface pattern, and color value. Therefore, a shadow pixel can be represented as a.x where x is the actual background color vector in 3-D RGB color space and a is a positive real number less than 1. In this paper, a shadow detection method based on two-dimensional (2-D) cepstrum is proposed. © 2009 SPIE.Item Open Access Wildfire detection using LMS based active learning(IEEE, 2009-04) Töreyin, B. Uğur; Çetin, A. EnisA computer vision based algorithm for wildfire detection is developed. The main detection algorithm is composed of four sub-algorithms detecting (i) slow moving objects, (ii) gray regions, (iii) rising regions, and (iv) shadows. Each algorithm yields its own decision as a real number in the range [-1,1] at every image frame of a video sequence. Decisions from subalgorithms are fused using an adaptive algorithm. In contrast to standard Weighted Majority Algorithm (WMA), weights are updated using the Least Mean Square (LMS) method in the training (learning) stage. The error function is defined as the difference between the overall decision of the main algorithm and the decision of an oracle, who is the security guard of the forest look-out tower. ©2009 IEEE.