Now showing items 1-20 of 243

    • 2D and 3D shape retrieval using skeleton filling rate 

      Sirin, Yahya; Demirci, Muhammed Fatih (Springer, 2017-03)
      As an increasing number of digital images are generated, a demand for an efficient and effective image retrieval mechanisms grows. In this work, we present a new skeleton-based algorithm for 2D and 3D shape retrieval. The ...
    • 3D Shape Recognition: Enhanced Skeletal Points 

      Sirin, Yahya; Demirci, Muhammed Fatih (IEEE, 2015)
      Digital video production is increasing day after day and the effectiveness and efficiency of the image recognition mechanism has became increasingly important. In this study, a new skeleton-based shape recognition algorithm, ...
    • Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach 

      Sezer, Ömer Berat; Özbayoğlu, Ahmet Murat (Elsevier Ltd, 2018-09)
      Computational intelligence techniques for financial trading systems have always been quite popular. In the last decade, deep learning models start getting more attention, especially within the image processing community. ...
    • Analysis and prediction in sparse and high dimensional text data: The case of Dow Jones stock market 

      Sert, Onur Can; Sahin, Salih Doruk; Özyer, Tansel; Alhajj, Reda (Elsevier B.V., 2020-05)
      In this research, we proposed a text analysis system to predict stock market movements using news and social media data. It is a scalable prediction system for sparse and high dimensional feature sets. Using the developed ...
    • An Analysis DRDoS Amplifiers in Europe 

      Ercan, Emre Murat; Selçuk, Ali Aydın (International Conference on Cyber Security and Computer Science, 2018-10)
      DRDoS is the new method of choice for denial of service attacks: Certain services running over UDP is chosen for the attack. Servers across the Internet are contacted by bots with the spoofed IP address of the victim host. ...
    • Analysis of Seam-Carving-Based Anonymization of Images Against PRNU Noise Pattern-Based Source Attribution 

      Dirik, Ahmet Emir; Sencar, Hüsrev Taha; Memon, Nasir (IEEE-INST Electrical Electronics Engineers Inc., 2014-12)
      The availability of sophisticated source attribution techniques raises new concerns about privacy and anonymity of photographers, activists, and human right defenders who need to stay anonymous while spreading their images ...
    • Analysis of the Effect of Image Resolution on Automatic Face Gender and Age Classification 

      Cerit, Betul; Boluk, S. Arda; Demirci, Muhammed Fatih (IEEE, 2016)
      In this paper, the effect of the image resolution for gender detection and age classification have been analyzed by conducting experiments with facial images that have 10 different image resolutions ranging from 2 x 1 to ...
    • Annotator rationales for labeling tasks in crowdsourcing 

      Kutlu, Mücahid; McDonnell, T.; Elsayed, T.c; Lease, M. (AI Access Foundation, 2020)
      When collecting item ratings from human judges, it can be difficult to measure and enforce data quality due to task subjectivity and lack of transparency into how judges make each rating decision. To address this, we ...
    • Anomaly detection in vehicle traffic with image processing and machine learning 

      Sarikan, S.S.; Özbayoğlu, Ahmet Murat (Elsevier B.V., 2018)
      Anomaly detection is an important part of an Intelligent Transportation System. In this study, image processing and machine learning techniques are used to detect anomalies in vehicle movements. These anomalies include ...
    • Anonymity in Multi-Instance Micro-Data Publication 

      Abul, Osman (SPRINGER, 2014)
      In this paper we study the problem of anonymity in multi-instance (MI) micro-data publication. The classical k-anonymity approach is shown to be insufficient and/or inappropriate for MI databases. Thus, it is extended to ...
    • Anonymous trace and revoke 

      Ak, Murat; Pehlivanoglu, Serdar; Selçuk, Ali Aydın (Elsevier, 2014-03-15)
      A broadcast encryption (BE) scheme is a method for encrypting messages in a way that only a set of privileged users can decrypt it. Anonymity in a BE system is to hide any information on the privileged set. This problem ...
    • Anti-cancer Drug Activity Prediction by Ensemble Learning 

      Tolan, Ertan; Tan, Mehmet (SCITEPRESS, 2016)
      Personalized cancer treatment is an ever-evolving approach due to complexity of cancer. As a part of personalized therapy, effectiveness of a drug on a cell line is measured. However, these experiments are backbreaking and ...
    • An Approach to Multi-Agent Pursuit Evasion Games Using Reinforcement Learning 

      Bilgin, Ahmet Tunc; Kadıoğlu-Ürtiş, Esra (IEEE, 2015)
      The game of pursuit-evasion has always been a popular research subject in the field of robotics. Reinforcement learning, which employs an agent's interaction with the environment, is a method widely used in pursuit-evasion ...
    • Are we secure from bots? Investigating vulnerabilities of botometer 

      Torusdağ, Buğra M.; Kutlu, Mücahid; Selçuk, Ali Aydın (Institute of Electrical and Electronics Engineers Inc., 2020-09)
      Social media platforms such as Twitter provide an incredibly efficient way to communicate with people. While these platforms have many benefits, they can also be used for deceiving people, spreading misinformation, ...
    • Armature Shape Optimization of an Electromagnetic Launcher Including Contact Resistance 

      Ceylan, Doğa; Güdelek, Mehmet Uğur; Keyşan, Ozan (Institute of Electrical and Electronics Engineers Inc., 2018-10)
      Barrel and pulsed power supply modules are two crucial parts of an electromagnetic launcher (EML), in terms of overall efficiency. One of the most important features of the barrel side is the armature geometry. In this ...
    • ArTest: The First Test Collection for Arabic Web Search with Relevance Rationales 

      Hasanain, M.; Barkallah, Y.; Suwaileh, R.; Kutlu, Mücahid; Elsayed, T. (Association for Computing Machinery, Inc, 2020-07)
      The scarcity of Arabic test collections has long hindered information retrieval (IR) research over the Arabic Web. In this work, we present ArTest, the first large-scale test collection designed for the evaluation of ...
    • An artificial neural network-based stock trading system using technical analysis and big data framework 

      Sezer, O.B.; Özbayoğlu, Ahmet Murat; Dogdu, E. (Association for Computing Machinery, Inc., 2017-04-13)
      In this paper, a neural network-based stock price prediction and trading system using technical analysis indicators is presented. The model developed first converts the financial time series data into a series of buy-sell-hold ...
    • Automated generation of attack graphs using NVD 

      Aksu, M. Ugur; Bıçakcı, Kemal; Dilek, M.H.; Özbayoğlu, Ahmet Murat; Tatlı, E.İ. (Association for Computing Machinery, Inc., 2018)
      Today’s computer networks are prone to sophisticated multi-step, multi-host attacks. Common approaches of identifying vulnerabilities and analyzing the security of such networks with naive methods such as counting the ...
    • Automated Image Matching and New Readings for Cyrus the Great's 547 BC Campaign in the Nabonidus Chronicle (BM 35382 = ABC 7) 

      Adali, Selim F.; Demirci, Muhammed Fatih; Özbayoğlu, Ahmet Murat (Vandenhoeck & Ruprecht, 2017-12)
      This article introduces an automated image matching technique called Scale Invariant Feature Transform (SIFT) as a tool to supplement the collation of problematic cuneiform signs. The Nabonidus Chronicle (II, 16), which ...
    • Automated Vehicle Classification with Image Processing and Computational Intelligence 

      Sarikan, Selim S.; Özbayoğlu, Ahmet Murat; Zilci, Oguzhan (ELSEVIER Science BV, 2017)
      Classification of vehicles is an important part of an Intelligent Transportation System. In this study, image processing and machine learning techniques are used to classify vehicles in dedicated lanes. Images containing ...