Now showing items 1-20 of 34

    • 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 ...
    • 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 ...
    • Boosting performance of directory-based cache coherence protocols with coherence bypass at subpage granularity and a novel on-chip page table 

      Soltaniyeh, M.; Kadayif, I.; Ozturk, O. (Association for Computing Machinery, Inc, 2016)
      Chip multiprocessors (CMPs) require effective cache coher-ence protocols as well as fast virtual-To-physical address trans-lation mechanisms for high performance. Directory-based cache coherence protocols are the ...
    • Chat mining for gender prediction 

      Kucukyilmaz, T.; Cambazoglu, B. B.; Aykanat, C.; Can, F. (Springer, 2006)
      The aim of this paper is to investigate the feasibility of predicting the gender of a text document's author using linguistic evidence. For this purpose, term- and style-based classification techniques are evaluated over ...
    • 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 ...
    • Comparative analysis of different approaches to target classification and localization with sonar 

      Ayrulu, B.; Barshan, B. (2001)
      The comparison of different classification and fusion techniques was done for target classification and localization with sonar. Target localization performance of artificial neural networks (ANN) was found to be better ...
    • Competitive and online piecewise linear classification 

      Ozkan H.; Donmez, M.A.; Pelvan O.S.; Akman, A.; Kozat, S.S. (2013)
      In this paper, we study the binary classification problem in machine learning and introduce a novel classification algorithm based on the 'Context Tree Weighting Method'. The introduced algorithm incrementally learns a ...
    • 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 ...
    • Detection of gamma responses in EEG signals 

      Tüfekçi, D.I.; Karakaş, S.; Arikan, O. (2006)
      In the detection of the existence of the early gamma response, subjective methods have been used. In this study, an automated gamma detection technique is developed based on the features obtained from the time - frequency ...
    • 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 ...
    • Estimating the chance of success in IVF treatment using a ranking algorithm 

      Güvenir, H. A.; Misirli, G.; Dilbaz, S.; Ozdegirmenci, O.; Demir, B.; Dilbaz, B. (Springer, 2015)
      In medicine, estimating the chance of success for treatment is important in deciding whether to begin the treatment or not. This paper focuses on the domain of in vitro fertilization (IVF), where estimating the outcome of ...
    • Exploiting interclass rules for focused crawling 

      Altingövde, I. S.; Ulusoy, Ö. (IEEE, 2004)
      A baseline crawler was developed at the Bilkent University based on a focused-crawling approach. The focused crawler is an agent that targets a particular topic and visits and gathers only a relevant, narrow Web segment ...
    • FAME: Face Association through Model Evolution 

      Golge, E.; Duygulu P. (IEEE Computer Society, 2014)
      We attack the problem of building classifiers for public faces from web images collected through querying a name. The search results are very noisy even after face detection, with several irrelevant faces corresponding to ...
    • 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 ...
    • Human activity recognition with different artificial neural network based classifiers 

      Catalbas B.; Morgul, O. (Institute of Electrical and Electronics Engineers Inc., 2017)
      Human Activity Recognition is a popular topic of research, with the importance it carries and its limited feature vector, to reach high success rates because of the difficulty faced in classification. With the increase of ...
    • Interactive training of advanced classifiers for mining remote sensing image archives 

      Aksoy, S.; Koperski, K.; Tusk, C.; Marchisio G. (2004)
      Advances in satellite technology and availability of down-loaded images constantly increase the sizes of remote sensing image archives. Automatic content extraction, classification and content-based retrieval have become ...
    • Large-scale cluster-based retrieval experiments on Turkish texts 

      Altingovde I.S.; Ozcan, R.; Ocalan H.C.; Can F.; Ulusoy Ö. (2007)
      We present cluster-based retrieval (CBR) experiments on the largest available Turkish document collection. Our experiments evaluate retrieval effectiveness and efficiency on both an automatically generated clustering ...
    • Machine-based learning system: classification of ADHD and non-ADHD participants 

      Öztoprak, H.; Toycan, M.; Alp, Y. K.; Arikan, O.; Doğutepe, E.; Karakaş S. (Institute of Electrical and Electronics Engineers Inc., 2017)
      Attention-deficit/hyperactivity disorder (ADHD) is the most frequent diagnosis among children who are referred to psychiatry departments. Although ADHD was discovered at the beginning of the 20th century, its diagnosis is ...