WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8653

Browse

Filters

2006 - 200932010 - 2019132020 - 202411

Settings

Language: search.filters.language.trPublisher: search.filters.publisher.Ieee

Search Results

Now showing 1 - 10 of 27
  • Conference Object
    Detection of Stylometric Writeprint From the Turkish Texts
    (Ieee, 2020) Canbay, Pelin; Sever, Hayri; Sezer, Ebru Akcapinar; Sever, Hayri; Bilgisayar Mühendisliği
    Authorship attribution studies aim to extract information about the author by analyzing the data in the text form. With the increase of anonymous authors in digital environments, the need for these works is increasing day by day. Although there exists lots of studies focuse on stylometric writeprint detection in different languages using different attributes, there is no standard feature set and detection algorithm to be evaluated in these studies. Giving priority to Turkish texts, in this study, which features are more distinctive for determining stylistic writeprint of text, and which methods will contribute to increase the success to be achieved are shown with experimental studies.
  • Conference Object
    Citation - Scopus: 13
    Predicting Flight Delays With Artificial Neural Networks: Case Study of an Airport
    (Ieee, 2017) Demir, Engin; Demir, Vahap Burhan
    Air transportation has an important place among transportation systems and it is indispensable for the flights to perform their voyages in scheduled time in order to ensure the comfort of passengers and controllability of operational costs. There are several reasons for flight delays like weather conditions, excessive intensity in air traffic, accidents or closed airfields, conditions that will lead to an increase in distances between planes and operational delays in ground services. In this study, using the data collected from the sensors located in the airport and the information about the flight, the goal is develop a machine learning model to estimate departure delays of flights using artificial neural networks.
  • Conference Object
    Parallelization of Sparsity-Driven Change Detection Method
    (Ieee, 2017) Ozgur, Atilla; Saran, Ayse Nurdan; Nar, Fatih
    In this study, Sparsity-driven Change Detection (SDCD) method, which has been proposed for detecting changes in multitemporal synthetic aperture radar (SAR) images, is parallelized to reduce the execution time. Parallelization of the SDCD is realized using OpenMP on CPU and CUDA on GPU. Execution speed of the parallelized SDCD is shown on real-world SAR images. Our experimental results show that the computation time of the parallel implementation brings significant speed-ups.
  • Conference Object
    Citation - Scopus: 1
    Localization of Semantic Category Classification in Fmri Images
    (Ieee, 2014) Alkan, Sarper; Yarman-Vural, Fatos T.
    In this study, we provide a methodology to localize the brain regions that contribute to semantic category classification. For this purpose we first cluster the data using spectral clustering. Then we extract local features within each cluster by using mesh-arc descriptors. Finally, we test the classification accuracy of each cluster against a hypothesis testing measure we provide here. We have found that, for the experimental task at hand, calcerine fissure and angular gyrus were most effective in classification. These results are shown to be match well with the nature of the experiment. Thus the validity of our approach is confirmed.
  • Conference Object
    Evaluation of 3d High Resolution Images Using Inexpensive Distributed Parallel System: Application Fields on Medical Images
    (Ieee, 2007) Eren, H.; Çelik, Ü.; Poyraz, M.
    In the telesurgery operations, images should be high resolution and processed in real time. It seems difficult to accomplish this process in real time using only one computer. In our study, we propose to get 3d scene images inside and outside of surgery environment in real time and transfer them into different places. As known, 3d reconstruction needs intensive calculations. Nowadays, using distributed parallel systems are getting increase. Therefore, we investigate the performance rates using a group of inexpensive inert computers which work as a distributed parallel system supposed to be established in a medical environment.
  • Conference Object
    Hierarchical Decision Making and Decision Fusion
    (Ieee, 2007) Beldek, Ulas; Leblebicioglu, Kemal
    In this study, a hierarchical decision making structure possessing a decision fusion technique is proposed in order to solve decision making problems efficiently. The proposed structure mainly depends on effects of the decisions made in the lower levels to decisions in the upper levels up to an activation degree. The proposed hierarchical structure is used for detecting the fault degrees for single and multiple fault scenarios artifically generated in a four tank system. The results obtained demonstrate the effectiveness of the proposed hierarchical decision making structure.
  • Conference Object
    Citation - Scopus: 2
    Approaches on the Selection of Web Cameras and Calibration Targets for Stereo Vision
    (Ieee, 2006) Eren, Haluk; Celik, Umit; Poyraz, Mustafa
    In this paper, it is studied on the calibration by using specified web cameras. The performance of 3D computer vision depends on the accuracy of camera parameters. Therefore, camera calibration is very crucial in stereo vision. In this study, the options and selection of the target object that is used by the process of camera calibration are reviewed and evaluated some results obtained by web cameras. Webcams' costs are low relatively to the other digital consumer cameras but cannot be acquired a high resolution image.
  • Conference Object
    Enhancing Trip Suggestions With Deep Learning Based Recommender System
    (Ieee, 2024) Erkal, Necati; Saran, Nurdan
    The importance of recommender systems has increased recently. It's due to the complexity of the data. It is becoming increasingly difficult to make recommendations that users might like. This is especially true in trip recommender systems, where recommending the next city is a challenging task. Deep learning has been shown to improve recommendation accuracy and handle complex data in various studies. This study presents new architectures, data, and hyperparameter tuning techniques for a deep learning-based trip recommender system. The study analyzes the algorithm and dataset of the NVIDIA Team's winning solution in the WSDM WebTour 2021 Challenge and proposes enhancements to it.
  • Conference Object
    A Novel Steganography Method for Halftone Images
    (Ieee, 2022) Ciftci, Efe; Sumer, Emre
    Steganography is the common name of methods that aim secret communication. In this conference proceeding, a novel steganography algorithm that hides plaintext payload in halftone images and a payload extraction algorithm that is suitable for messages hidden using this steganography method is presented. Our steganography algorithm uses a modified pattern-based halftone image generation procedure and distributes the payload into multiple output images. The proposed method has proven to be secure and able to hide large payloads. According to the objective and subjective evaluations made, it was seen that the proposed method produces promising results.
  • Conference Object
    Controller Design for Cacc With Time-Varying Communication Delays
    (Ieee, 2023) Soysal, Gokhan; Schmidt, Klaus Werner; Bingol, Hilal
    Cooperative Adaptive Cruise Control (CACC) aims at the safe and comfortable travel of vehicles at short distances in the form of platoons. Hereby, it is generally desired to attenuate disturbances along vehicles in a platoon, which is captured by different string stability conditions. In this paper, we focus on L-infinity string stability. This condition ensures reducing the magnitude of the acceleration signal along the platoon, which helps to avoid actuator saturation and increases driving comfort. Since the performance of CACC is adversely affected by time-varying communication and actuator delays, we develop the first controller design method for L-infinity-string stability, combining the Lyapunov-Krasovskii method and our custom bisection algorithm. Simulation experiments demonstrate the effectiveness of our method.