Ph.D. Candidate Electrical and Electronics Engineering / AKDENIZ UNIVERSITY +90 242 227 4400 (internal 4354) gurkancelik@akdeniz.edu.tr |
Gurkan Celik is Ph.D. candidate at Akdeniz University, Turkey. He received his M.Sc. degree in Electrical & Electronics Engineering from Akdeniz University, Turkey (2019) and B.Sc. degree in Electronics & Communication Engineering from Kocaeli University, Turkey (2015). During his bachelor he did two internships abroad. First is with IAESTE Programme at Electronics and Communication Engineering in Karunya University, India, aiming to separate mixed voices in the environment by using signal processing, supervised by Asst. Prof. Dr. Sugumar Durai. Second is with ERASMUS Internship at Instituto de Telecomunicações in Instituto Politecnico de Leiria, Portugal, aiming to trace melanoma disease course by using medical image processing techniques, supervised by Prof. Dr. Sérgio Faria. He is currently research assistant at ComNets Lab working on IoT, WSNs and localization techniques. He contributed 1 article, 1 book chapter and 3 conference papers.
EDUCATION
(2019 – Present) Akdeniz University, Institute of Science and Technology, Electrical and Electronics Engineering
(2017–2019) Akdeniz University, Institute of Science and Technology, Electrical and Electronics Engineering (91.3/100)
(2011–2015) Kocaeli University, Electronics and Communication Engineering (76/100)
DISSERTATIONS
The increasing communication burden and energy consumption, changing security and user needs together with the developing technology require the transmission units to display intelligent behaviors while communicating with each other. To accomplish this, the network components for storing, processing and transmitting data; there is a need to evaluate the network situation and to organize the communication with each other well. For this purpose, optimized data distribution nodes are required within the networks that provide intelligent and low-cost data transmission, making their deployment efficient. In this study, recommendations for positioning methods in terms of interoperability, performance, resource management and innovative integrated platforms that can meet various user expectations and data distribution techniques were made. ZigBee based nodes for real environment testing were designed and produced. Results of measurements that check the energy status of the modules on the network in a smart data distribution system for the next generation internet and take into account their distance from each other. With the experiments; time of arrival (ToA) and the received signal strength indicator (RSSI) methods are compared. The findings indicate that in ToA based measurements are on average 1.13 times lower under outdoor conditions and 1.17 times higher under indoor conditions. RSSI based measurements on average 2.4 and under indoor conditions 2.6 times higher under outdoor conditions than the reference distance. The difference of the ToA values gives more accurate results for longer distances, so the estimates are closer to the expected value as the distance increases. Several filtering and statistical methods were used to reduce the error rate of these values.
An image mosaic is a panoramic image generated by assembling sequential images belong to the same scene. This method is mainly used in mapping applications, the evaluation of the images acquired from unmanned aerial vehicles (UAV), and various computer vision applications. In this study, a novel blending method is proposed for automatic and seamless mosaicing of photos taken by an unprofessional digital camera. For the correction of consistent seams occurred during the mosaicing, the color differences around the overlapping regions are tried to fix. For this purpose, instead of the new image frame is to be assigned are averaged with the previous images frame. The intensity values are averaged and finally, the average values of color differences are applied to overlapping regions. Besides, the code is performed for the corresponding boundary regions in order to reduce the seams. The results show the effectiveness, computational complexity and accuracy of the algorithm. Consequently, these implementations realizing an image mosaicing implementation, have been examined and verified with the experimental results. The results of study indicate that the seams, which occurs after mosaicing, can be substantially reduced or completely eliminated. Besides, it is observed that the illumination differences are minimized. The panoramic image is obtained by applying feature extraction, image matching, outlier point detection and removal, respectively homography estimation and image fusion on the images taken as input.
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