Filters

2009 - 200912010 - 20191
Reset filters

Settings

Author: Yazici, AdnanCOAR Access Rights: open access

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Article
    Citation - WoS: 16
    Citation - Scopus: 25
    An Intelligent Fuzzy Object-Oriented Database Framework for Video Database Applications
    (Elsevier, 2009) Ozgur, Nezihe Burcu; Koyuncu, Murat; Yazici, Adnan
    Video database applications call for flexible and powerful modeling and querying facilities, which require an integration or interaction between database and knowledge-based technologies. It is also necessary for many real life video database applications to incorporate uncertainty, which naturally occurs due to the complex and subjective semantic content of video data. In this study, firstly, we introduce a fuzzy conceptual data model to represent the semantic content of video data. For that purpose, UML (unified modeling language) is utilized and extended to represent uncertain information along with video specific properties. Secondly, we present an intelligent fuzzy object-oriented database framework for video database applications. The introduced fuzzy conceptual model is used in this framework, which provides modeling of complex and rich semantic content and knowledge of video data including uncertainty. Moreover, it supports various flexible queries including (fuzzy) semantic, temporal and (fuzzy) spatial queries, based on the video data model. We think that the presented conceptual data model and the framework can be used for any video database application. (C) 2009 Elsevier B.V. All rights reserved.
  • Thumbnail Image
    Article
    Citation - WoS: 30
    Citation - Scopus: 48
    A Fusion-Based Framework for Wireless Multimedia Sensor Networks in Surveillance Applications
    (Ieee-inst Electrical Electronics Engineers inc, 2019) Yazici, Adnan; Koyuncu, Murat; Sert, Seyyit Alper; Yilmaz, Turgay
    Multimedia sensors enable monitoring applications to obtain more accurate and detailed information. However, the development of efficient and lightweight solutions for managing data traffic over wireless multimedia sensor networks (WMSNs) has become vital because of the excessive volume of data produced by multimedia sensors. As part of this motivation, this paper proposes a fusion-based WMSN framework that reduces the amount of data to be transmitted over the network by intra-node processing. This framework explores three main issues: 1) the design of a wireless multimedia sensor (WMS) node to detect objects using machine learning techniques; 2) a method for increasing the accuracy while reducing the amount of information transmitted by the WMS nodes to the base station, and; 3) a new cluster-based routing algorithm for the WMSNs that consumes less power than the currently used algorithms. In this context, a WMS node is designed and implemented using commercially available components. In order to reduce the amount of information to be transmitted to the base station and thereby extend the lifetime of a WMSN, a method for detecting and classifying objects on three different layers has been developed. A new energy-efficient cluster-based routing algorithm is developed to transfer the collected information/data to the sink. The proposed framework and the cluster-based routing algorithm are applied to our WMS nodes and tested experimentally. The results of the experiments clearly demonstrate the feasibility of the proposed WMSN architecture in the real-world surveillance applications.