Now showing items 1-20 of 47

    • 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 ...
    • Adaptive ensemble learning with confidence bounds for personalized diagnosis 

      Tekin, C.; Yoon, J.; Schaar, M. V. D. (AI Access Foundation, 2016)
      With the advances in the field of medical informatics, automated clinical decision support systems are becoming the de facto standard in personalized diagnosis. In order to establish high accuracy and confidence in ...
    • Adaptive Hierarchical Space Partitioning for Online Classification 

      Fatih Kilic, O.; Denizcan Vanli, N.; Ozkan, H.; Delibalta, I.; Kozat, S. S. (European Signal Processing Conference, EUSIPCO, 2016)
      We propose an online algorithm for supervised learning with strong performance guarantees under the empirical zero-one loss. The proposed method adaptively partitions the feature space in a hierarchical manner and generates ...
    • Application of the RIMARC algorithm to a large data set of action potentials and clinical parameters for risk prediction of atrial fibrillation 

      Ravens, U.; Katircioglu-Öztürk, D.; Wettwer, E.; Christ, T.; Dobrev, D.; Voigt, N.; Poulet, C.; Loose, S.; Simon, J.; Stein, A.; Matschke, K.; Knaut, M.; Oto, E.; Oto, A.; Güvenir, H. A. (Springer, 2015)
      Ex vivo recorded action potentials (APs) in human right atrial tissue from patients in sinus rhythm (SR) or atrial fibrillation (AF) display a characteristic spike-and-dome or triangular shape, respectively, but variability ...
    • 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 categorization of ottoman literary texts by poet and time period 

      Can, E.F.; Can F.; Duygulu P.; Kalpakli, M. (2012)
      Millions of manuscripts and printed texts are available in the Ottoman language. The automatic categorization of Ottoman texts would make these documents much more accessible in various applications ranging from historical ...
    • Big-data streaming applications scheduling based on staged multi-armed bandits 

      Kanoun, K.; Tekin, C.; Atienza, D.; Van Der Schaar, M. (Institute of Electrical and Electronics Engineers, 2016)
      Several techniques have been recently proposed to adapt Big-Data streaming applications to existing many core platforms. Among these techniques, online reinforcement learning methods have been proposed that learn how to ...
    • Boosted LMS-Based Piecewise Linear Adaptive Filters 

      Kari, D.; Marivani, I.; Delibalta, I.; Kozat, S.S. (European Signal Processing Conference, EUSIPCO, 2016)
      We introduce the boosting notion extensively used in different machine learning applications to adaptive signal processing literature and implement several different adaptive filtering algorithms. In this framework, we ...
    • Cell-graph mining for breast tissue modeling and classification 

      Bilgin, C.; Demir, C.; Nagi, C.; Yener, B. (2007)
      We consider the problem of automated cancer diagnosis in the context of breast tissues. We present graph theoretical techniques that identify and compute quantitative metrics for tissue characterization and classification. ...
    • Classification by voting feature intervals 

      Demiröz, G.; Güvenir, A. H. (Springer, 1997)
      A new classification algorithm called VFI (for Voting Feature Intervals) is proposed. A concept is represented by a set of feature intervals on each feature dimension separately. Each feature participates in the classification ...
    • 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 ...
    • Computer vision based text and equation editor for LATEX 

      Öksüz Ö.; Güdükbay, U.; Çetin, E. (2004)
      In this paper, we present a computer vision based text and equation editor for LATEX. The user writes text and equations on paper and a camera attached to a computer records actions of the user. In particular, positions ...
    • Çağrı merkezi metin madenciliği yaklaşımı 

      Yigit, I. O.; Ates, A. F.; Guvercin, M.; Ferhatosmanoglu, H.; Gedik, B. (Institute of Electrical and Electronics Engineers Inc., 2017)
      Günümüzde çağrı merkezlerindeki görüşme kayıtlarının sesten metne dönüştürülebilmesi görüşme kaydı metinleri üzerinde metin madenciliği yöntemlerinin uygulanmasını mümkün kılmaktadır. Bu çalışma kapsamında görüşme ...
    • 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 ...
    • Distance-based classification methods 

      Ekin, O.; Hammer, P. L.; Kogan, A.; Winter, P. (Taylor & Francis, 1999)
      Given a set of points in a Euclidean space, and a partitioning of this 'training set' into two or more subsets ('classes'), we consider the problem of identifying a 'reasonable' assignment of another point in the Euclidean ...
    • The effect of uncertainty on learning in game-like environments 

      Ozcelik, E.; Cagiltay, N. E.; Ozcelik, N. S. (Pergamon Press, 2013)
      Considering the role of games for educational purposes, there has an increase in interest among educators in applying strategies used in popular games to create more engaging learning environments. Learning is more fun and ...
    • An energy efficient additive neural network 

      Afrasiyabi, A.; Nasir, B.; Yildiz, O.; Vural, F. T. Y.; Cetin, A. E. (Institute of Electrical and Electronics Engineers Inc., 2017)
      In this paper, we propose a new energy efficient neural network with the universal approximation property over space of Lebesgue integrable functions. This network, called additive neural network, is very suitable for ...
    • Ensemble of multiple instance classifiers for image re-ranking 

      Sener F.; Ikizler-Cinbis, N. (Elsevier Ltd, 2014)
      Text-based image retrieval may perform poorly due to the irrelevant and/or incomplete text surrounding the images in the web pages. In such situations, visual content of the images can be leveraged to improve the image ...
    • Extraction of sparse spatial filters using Oscillating Search 

      Onaran I.; Firat Ince, N.; Abosch, A.; Enis Cetin, A. (2012)
      Common Spatial Pattern algorithm (CSP) is widely used in Brain Machine Interface (BMI) technology to extract features from dense electrode recordings by using their weighted linear combination. However, the CSP algorithm, ...
    • Generalizing predicates with string arguments 

      Cicekli, I.; Cicekli, N. K. (Springer New York LLC, 2006-06)
      The least general generalization (LGG) of strings may cause an over-generalization in the generalization process of the clauses of predicates with string arguments. We propose a specific generalization (SG) for strings to ...