Now showing items 1-20 of 40

    • Activity recognition invariant to sensor orientation with wearable motion sensors 

      Yurtman, A.; Barshan, B. (MDPI AG, 2017)
      Most activity recognition studies that employ wearable sensors assume that the sensors are attached at pre-determined positions and orientations that do not change over time. Since this is not the case in practice, it is ...
    • Authorship attribution: performance of various features and classification methods 

      Bozkurt, I. N.; Bağlioğlu, Ö.; Uyar, E. (2007)
      Authorship attribution is the process of determining the writer of a document. In literature, there are lots of classification techniques conducted in this process. In this paper we explore information retrieval methods ...
    • Automatic radar antenna scan type recognition in electronic warfare 

      Barshan, B.; Eravci, B. (Institute of Electrical and Electronics Engineers, 2011-10-04)
      We propose a novel and robust algorithm for antenna scan type (AST) recognition in electronic warfare (EW). The stages of the algorithm are scan period estimation, preprocessing (normalization, resampling, averaging), ...
    • Autonomous multiple teams establishment for mobile sensor networks by SVMs within a potential field 

      Nazlibilek, S. (2012)
      In this work, a new method and algorithm for autonomous teams establishment with mobile sensor network units by SVMs based on task allocations within a potential field is proposed. The sensor network deployed into the ...
    • Bilkent-RETINA at retrieving diverse social images task of MediaEval 2014 

      Saraç, Mustafa İlker; Duygulu Pınar (CEUR-WS, 2014-10)
      This paper explains the approach proposed by Bilkent - RETINA team for the Retrieving Diverse Social Images task of MediaEval 2014 [1]. We develop a framework which rst removes outliers using one-class support vector ...
    • Canlı hücre bölütlemesi için gözeticili öğrenme modeli 

      Koyuncu, Can Fahrettin; Durmaz, İrem; Çetin-Atalay, Rengül; Gündüz-Demir, Çiğdem (IEEE Computer Society, 2014-04)
      Automated cell imaging systems have been proposed for faster and more reliable analysis of biological events at the cellular level. The first step of these systems is usually cell segmentation whose success affects the ...
    • Carcinoma cell line discrimination in microscopic images using unbalanced wavelets 

      Keskin F.; Suhre, A.; Erşahin, T.; Çetin-Atalay R.; Çetin, A. E. (2012)
      Cancer cell lines are widely used for research purposes in laboratories all over the world. In this paper, we present a novel method for cancer cell line image classification, which is very costly by conventional methods. ...
    • Cepstrum based feature extraction method for fungus detection 

      Yorulmaz O.; Pearson, T.C.; Çetin, A.E. (2011)
      In this paper, a method for detection of popcorn kernels infected by a fungus is developed using image processing. The method is based on two dimensional (2D) mel and Mellin-cepstrum computation from popcorn kernel images. ...
    • Classification of regional ionospheric disturbance based on machine learning techniques 

      Terzi, M. B.; Arikan, O.; Karatay S.; Arikan, F.; Gulyaeva T. (European Space Agency, 2016)
      In this study, Total Electron Content (TEC) estimated from GPS receivers is used to model the regional and local variability that differs from global activity along with solar and geomagnetic indices. For the automated ...
    • Classifying fonts and calligraphy styles using complex wavelet transform 

      Bozkurt, A.; Duygulu P.; Cetin, A.E. (Springer-Verlag London Ltd, 2015)
      Recognizing fonts has become an important task in document analysis, due to the increasing number of available digital documents in different fonts and emphases. A generic font recognition system independent of language, ...
    • Classifying human leg motions with uniaxial piezoelectric gyroscopes 

      Tunçel O.; Altun, K.; Barshan, B. (2009)
      This paper provides a comparative study on the different techniques of classifying human leg motions that are performed using two low-cost uniaxial piezoelectric gyroscopes worn on the leg. A number of feature sets, extracted ...
    • A comparative study of classification methods for fall detection 

      Catalbas, B.; Yucesoy, B.; Secer G.; Aslan, M. (IEEE Computer Society, 2014)
      A comparative study of various fall detection algorithms based upon measurements of a wearable tri-axial accelerometer unit is presented in this paper. Least squares support vector machine, neural network and rule-based ...
    • Comparative study on classifying human activities with miniature inertial and magnetic sensors 

      Altun, K.; Barshan, B.; Tunçel, O. (Elsevier, 2010)
      This paper provides a comparative study on the different techniques of classifying human activities that are performed using body-worn miniature inertial and magnetic sensors. The classification techniques implemented and ...
    • Covariance matrix-based fire and flame detection method in video 

      Habiboğlu, Y. H.; Günay, O.; Çetin, A. E. (Springer, 2011-09-17)
      This paper proposes a video-based fire detection system which uses color, spatial and temporal information. The system divides the video into spatio-temporal blocks and uses covariance-based features extracted from these ...
    • Detection of acute myocardial ischemia based on support vector machines 

      Terzi, M. B.; Arikan, O. (Institute of Electrical and Electronics Engineers, 2018)
      In patients with acute myocardial ischemia, chest pains together with changes in ST/T sections of ECG signal occur before the start of myocardial infarction. In this study, in order to diagnose acute myocardial ischemia, ...
    • Detection of empty hazelnuts from fully developed nuts by impact acoustics 

      Onaran, I.; Dulek, B.; Pearson, T. C.; Yardimci, Y.; Cetin, A. E. (2005)
      Shell-kernel weight ratio is the main determinate of quality and price of hazelnuts. Empty hazelnuts and nuts containing undeveloped kernels may also contain mycotoxin producing molds, which can cause cancer. A prototype ...
    • Detection of fungal damaged popcorn using image property covariance features 

      Yorulmaz, O.; Pearson, T. C.; Çetin, A. (Elsevier, 2012)
      Covariance-matrix-based features were applied to the detection of popcorn infected by a fungus that causes a symptom called " blue-eye" . This infection of popcorn kernels causes economic losses due to the kernels' poor ...
    • Early diagnosis of acute coronary syndromes with automatic ST/T classifier 

      Terzi, M. B.; Arikan, O.; Abaci, A.; Candemir, M.; Dedoğlu, M. (Institute of Electrical and Electronics Engineers Inc., 2014)
      In patients with acute coronary syndrome, temporary chest pains together with changes in ECG ST segment and T wave occur shortly before the start of myocardial infarction. In order to diagnose acute coronary syndromes ...
    • Fall detection using single-tree complex wavelet transform 

      Yazar, A.; Keskin, F.; Töreyin, B. U.; Çetin, A. E. (Elsevier, 2013)
      The goal of Ambient Assisted Living (AAL) research is to improve the quality of life of the elderly and handicapped people and help them maintain an independent lifestyle with the use of sensors, signal processing and ...
    • Feature extraction and classification in a two-state brain-computer interface 

      Altindis, F.; Yilmaz, B. (Institute of Electrical and Electronics Engineers Inc., 2017)
      Brain Computer Interface (BCI) technology is used to help patients who do not have control over motor neurons such as ALS or paralyzed patients, to communicate with outer world. This work aims to classify motor imageries ...