Now showing items 1-15 of 15

    • Akut koroner sendromun destek vektör makinelerine ve EKG’ye dayalı tespiti 

      Terzi, Merve Begüm; Arıkan, Orhan (IEEE, 2019-04)
      Akut koroner sendroma (AKS) sahip hastalarda, miyokard infarktüsü başlangıcından önce geçici göğüs ağrıları ile birlikte EKG sinyalinin ST segmentinde ve T dalgasında değişiklikler meydana gelmektedir. Bu çalışmada, AKS’nin ...
    • Anomaly detection with sparse unmixing and gaussian mixture modeling of hyperspectral images 

      Erdinç, Acar (Bilkent University, 2015-07)
      One of the main applications of hyperspectral image analysis is anomaly detection where the problem of interest is the detection of small rare objects that stand out from their surroundings. A common approach to anomaly ...
    • Data imputation through the identification of local anomalies 

      Ozkan, H.; Pelvan, O. S.; Kozat, S. S. (Institute of Electrical and Electronics Engineers Inc., 2015)
      We introduce a comprehensive and statistical framework in a model free setting for a complete treatment of localized data corruptions due to severe noise sources, e.g., an occluder in the case of a visual recording. Within ...
    • Efficient NP tests for anomaly detection over birth-death type DTMCs 

      Ozkan, H.; Ozkan, F.; Delibalta, I.; Kozat, S. S. (Springer New York LLC, 2018)
      We propose computationally highly efficient Neyman-Pearson (NP) tests for anomaly detection over birth-death type discrete time Markov chains. Instead of relying on extensive Monte Carlo simulations (as in the case of the ...
    • Flexible test-bed for unusual behavior detection 

      Petrás I.; Beleznai, C.; Dedeolğu, Yiğithan; Pards, M.; Kovács L.; Szlávik, Z.; Havasi L.; Szirányi, T.; Töreyin, B. Uğur; Güdükbay, Uğur; Çetin, A.hmet Enis; Canton-Ferrer, C. (ACM, 2007-07)
      Visual surveillance and activity analysis is an active research field of computer vision. As a result, there are several different algorithms produced for this purpose. To obtain more robust systems it is desirable to ...
    • Keyframe labeling technique for surveillance event classification 

      Şaykol, E.; Baştan M.; Güdükbay, Uğur; Ulusoy, Özgür (S P I E - International Society for Optical Engineering, 2010)
      The huge amount of video data generated by surveillance systems necessitates the use of automatic tools for their efficient analysis, indexing, and retrieval. Automated access to the semantic content of surveillance videos ...
    • Koroner arter hastalığının destek vektör makineleri ve Gauss karışım modeli ile tespiti 

      Terzi, Merve Begüm; Arıkan, Orhan (IEEE, 2019-04)
      Bu çalışmada, koroner arter hastalığının (KAH) gürbüz tespitini gerçekleştirmek amacıyla EKG’deki anomalileri güncel sinyal işleme ve makine ögrenmesi yöntemlerini kullanarak tespit eden bir teknik geliştirilmiştir. Bu ...
    • A novel anomaly detection approach based on neural networks 

      Ergen, Tolga; Kerpiççi, Mine (Institute of Electrical and Electronics Engineers, 2018)
      In this paper, we introduce a Long Short Term Memory (LSTM) networks based anomaly detection algorithm, which works in an unsupervised framework. We first introduce LSTM based structure for variable length data sequences ...
    • Online anomaly detection in case of limited feedback with accurate distribution learning 

      Marivani, Iman; Kari, Dariush; Kurt, Ali Emirhan; Manış, Eren (IEEE, 2017)
      We propose a high-performance algorithm for sequential anomaly detection. The proposed algorithm sequentially runs over data streams, accurately estimates the nominal distribution using exponential family and then declares ...
    • Online anomaly detection under Markov statistics with controllable type-I error 

      Ozkan, H.; Ozkan, F.; Kozat, S. S. (Institute of Electrical and Electronics Engineers Inc., 2016)
      We study anomaly detection for fast streaming temporal data with real time Type-I error, i.e., false alarm rate, controllability; and propose a computationally highly efficient online algorithm, which closely achieves a ...
    • Online anomaly detection with minimax optimal density estimation in nonstationary environments 

      Gokcesu, K.; Kozat, S. S. (Institute of Electrical and Electronics Engineers, 2018)
      We introduce a truly online anomaly detection algorithm that sequentially processes data to detect anomalies in time series. In anomaly detection, while the anomalous data are arbitrary, the normal data have similarities ...
    • Online learning under adverse settings 

      Özkan, Hüseyin (Bilkent University, 2015-05)
      We present novel solutions for contemporary real life applications that generate data at unforeseen rates in unpredictable forms including non-stationarity, corruptions, missing/mixed attributes and high dimensionality. ...
    • Sequential outlier detection based on incremental decision trees 

      Gökçesu, Kaan; Neyshabouri, Mohammadreza Mohaghegh; Gökçesu, Hakan; Serdar, Süleyman (IEEE, 2019-02-15)
      We introduce an online outlier detection algorithm to detect outliers in a sequentially observed data stream. For this purpose, we use a two-stage filtering and hedging approach. In the first stage, we construct a multimodal ...
    • Spoofing attack detection by anomaly detection 

      Fatemifar, S.; Arashloo, Shervin Rahimzadeh; Awais, M.; Kittler, J. (Institute of Electrical and Electronics Engineers Inc., 2019)
      Spoofing attacks on biometric systems can seriously compromise their practical utility. In this paper we focus on face spoofing detection. The majority of papers on spoofing attack detection formulate the problem as a two ...
    • What is usual in unusual videos? trajectory snippet histograms for discovering unusualness 

      İşcen, Ahmet; Armağan, Anıl; Duygulu, Pınar (IEEE, 2014-06)
      Unusual events are important as being possible indicators of undesired consequences. Moreover, unusualness in everyday life activities may also be amusing to watch as proven by the popularity of such videos shared in social ...