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ÜLKÜ, EYÜP EMRE

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ÜLKÜ

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EYÜP EMRE

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2017 - 20192
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Author: DEMİR, ÖNDER × Has files: true ×

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    PublicationOpen Access
    Sharing Location Information in Multi-UAV Systems by Common Channel Multi-Token Circulation Method in FANETs
    (KAUNAS UNIV TECHNOLOGY, 2019-02-12) DOĞAN, BUKET; Ulku, Eyup Emre; Dogan, Buket; Demir, Onder; Bekmezci, Ilker
    Unmanned Aerial Vehicle (UAV) technology is being used increasingly for military and civilian purposes. The primary reason for this increase is that UAVs eliminate the risk to human life in difficult and dangerous missions, are cost effective, and easily are deployed. Developments in UAV technology and decreasing costs have increased UAV usage. However, when multiple UAVs are deployed, inter UAV communication becomes complicated. For this reason, communication in multi-UAV systems is the most important problem that needs to be solved. To enable communication among UAVs without infrastructure support, a Flying Ad Hoc Network (FANET) is used. A FANET provides UAVs to fly in tandem without colliding. To ensure coordinated flight, UAVs require the location information of other UAVs. In this study, we developed a common channel multi-token circulation protocol to share location information in multi-UAV systems that communicate using a FANET. The proposed method ensures that UAVs in multi-UAV systems know each other's coordinate information with minimum error.
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    PublicationOpen Access
    Fault detection of fabrics using image processing methods
    (PAMUKKALE UNIV, 2017) ÜLKÜ, EYÜP EMRE; Yildiz, Kazim; Demir, Onder; Ulku, Eyup Emre
    This paper presents a computer aided detection (CAD) system which uses wiener filter based approach for detection of defects in poplin fabric. The defective fabric images are taken with the help of the digital camera. The developed system consists of three phases, including preprocessing, segmentation and detection of fabric defect In preprocessing phase, a RGB to gray level conversion and image enhancement operations were applied to digital camera images. In segmentation phase, background of the gray level image segmented using morphologic operations. Then, segmented image was converted to binary image to facilitate fabric defect detection process. Fabric defect detection was performed using wiener filter in the detection phase of the system. Wiener filter is applied to binary level image to eliminate structures which are not defect The developed detection system applied on defective poplin images for detection. The obtained results on different kinds of fabric defects show that the proposed algorithm gives promising results.