• About
  • Policies
  • What is open access
  • Library
  • Contact
Advanced search
      View Item 
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Engineering
      • Department of Electrical and Electronics Engineering
      • View Item
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Engineering
      • Department of Electrical and Electronics Engineering
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Entropi fonsiyonuna dayalı uyarlanır karar tümleştirme yapısı

      Thumbnail
      View / Download
      2.4 Mb
      Author
      Günay, Osman
      Töreyin, B. U.
      Köse, Kıvanç
      Çetin, A. Enis
      Date
      2012-04
      Source Title
      20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedings
      Pages
      [1] - [4]
      Language
      Turkish
      Type
      Conference Paper
      Item Usage Stats
      141
      views
      75
      downloads
      Abstract
      Bu bildiride, resim analizi ve bilgisayarla görü uygulamalarında kullanılmak üzere entropi fonksiyonuna dayanan uyarlanır karar tümleştirme yapısı geliştirilmiştir. Bu yapıda bileşik algoritma, herbiri güven derecesini temsil eden sıfır merkezli bir gerçek sayı olarak kendi kararını oluşturan birçok alt algoritmadan meydana gelir. Karar değerleri, çevrimiçi olarak alt algoritmaları tanımlayan dışbukey kümelerin üzerine entropik izdüşümler yapmaya dayalı bir aktif tümleştirme yöntemi ile güncellenen ağırlıklar kullanılarak doğrusal olarak birleştirilir. Bu yapıda genelde bir insan olan bir uzman da bulunur ve karar tümleştirme algoritmasına geribesleme sağlar. Önerilen karar tümleştirme algoritmasının performansı geliştirdigimiz video tabanlı bir orman yangını bulma sistemi kullanılarak test edilmiştir.
       
      In this paper, an entropy functional based online adaptive decision fusion framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several sub-algorithms, each of which yields its own decision as a real number centered around zero, representing the confidence level of that particular sub-algorithm. Decision values are linearly combined with weights which are updated online according to an active fusion method based on performing entropic projections onto convex sets describing sub-algorithms. It is assumed that there is an oracle, who is usually a human operator, providing feedback to the decision fusion method. A video based wildfire detection system was developed to evaluate the performance of the decision fusion algorithm.
      Keywords
      Active fusion
      Compound algorithm
      Computer vision applications
      Confidence levels
      Decision fusion
      Decision fusion methods
      Decision value
      Decision-fusion algorithms
      Entropy functional
      Human operator
      Projections onto convex sets
      Real number
      Wildfire detection
      Computer vision
      Entropy
      Set theory
      Signal processing
      Algorithms
      Permalink
      http://hdl.handle.net/11693/28193
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/SIU.2012.6204712
      Collections
      • Department of Electrical and Electronics Engineering 3650
      Show full item record

      Browse

      All of BUIRCommunities & CollectionsTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartmentsThis CollectionTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartments

      My Account

      Login

      Statistics

      View Usage StatisticsView Google Analytics Statistics

      Bilkent University

      If you have trouble accessing this page and need to request an alternate format, contact the site administrator. Phone: (312) 290 1771
      © Bilkent University - Library IT

      Contact Us | Send Feedback | Off-Campus Access | Admin | Privacy