Now showing items 1288-1307 of 1363

    • Turkish keyphrase extraction using multi-criterion ranking 

      Özdemir, Bahadır; Çiçekli, İlyas (IEEE, 2009-09)
      Keyphrases have been extensively used for indexing and searching in databases and information retrieval systems. In addition, they provide useful information about semantic content of a document. In this paper, we propose ...
    • Tutorial services for students at Bilkent University an evaluation after five years 

      Çelik, B. Keyik; Özdemir, B. Uslu; Verhoeven, John M (Sense Publishers, 2008)
      To realize our mission as academic coordinators for engineering students at Bilkent University, we facilitate in different ways tutorial services. These focus on the first year courses for physics, mathematics and computer ...
    • Tutorial: Stream processing optimizations 

      Schneider, S.; Hirzel, M.; Gedik, Buğra (ACM, 2013)
      This tutorial starts with a survey of optimizations for streaming applications. The survey is organized as a catalog that introduces uniform terminology and a common categorization of optimizations across disciplines, such ...
    • Twitter sentiment analysis, 3-way classification: positive, negative or neutral? 

      Çeliktuğ, Mestan Fırat (Institute of Electrical and Electronics Engineers Inc., 2019)
      People face with the huge amount of information on each day with the advent of big data era. The data amount stored and processed by Facebook, Twitter and other big social networks store (e.g. Instagram) is massive in those ...
    • The two (computational) faces of AI 

      Davenport, D. (Springer International Publishing, 2013)
      There is no doubt that AI research has made significant progress, both in helping us understand how the human mind works and in constructing ever more sophisticated machines. But, for all this, its conceptual foundations ...
    • Two learning approaches for protein name extraction 

      Tatar, S.; Cicekli, I. (Academic Press, 2009)
      Protein name extraction, one of the basic tasks in automatic extraction of information from biological texts, remains challenging. In this paper, we explore the use of two different machine learning techniques and present ...
    • Two novel multiway circuit partitioning algorithms using relaxed locking 

      Dasdan, A.; Aykanat, Cevdet (IEEE, 1997)
      All the previous Kernighan-Lin-based (KL-based) circuit partitioning algorithms employ the locking mechanism, which enforces each cell to move exactly once per pass. In this paper, we propose two novel approaches for ...
    • Two-dimensional packing algorithms for layout of disconnected graphs 

      Dogrusoz, U. (Elsevier, 2002)
      We present and contrast several efficient two-dimensional packing algorithms for specified aspect ratio. These near-linear algorithms are based on strip packing, tiling, and alternate-bisection methodologies and can be ...
    • Two-level description of Turkish morphology 

      Oflazer, K. (Oxford University Press, 1994)
      This paper describes a full two-level morphological description of Turkish word structures. The description has been implemented using the PC-KIMMO environment and is based on a root word lexicon of about 23,000 root words. ...
    • Two-person interaction recognition via spatial multiple instance embedding 

      Sener F.; Ikizler-Cinbis, N. (Academic Press Inc., 2015)
      Abstract In this work, we look into the problem of recognizing two-person interactions in videos. Our method integrates multiple visual features in a weakly supervised manner by utilizing an embedding-based multiple instance ...
    • Two-tier tissue decomposition for histopathological image representation and classification 

      Gultekin, T.; Koyuncu, C. F.; Sokmensuer, C.; Gunduz Demir, C. (Institute of Electrical and Electronics Engineers, 2015)
      In digital pathology, devising effective image representations is crucial to design robust automated diagnosis systems. To this end, many studies have proposed to develop object-based representations, instead of directly ...
    • Understanding and predicting trends in urban freight transport 

      Mrazovic, P.; Eravci, Bahaeddin; Larriba-Pey, J. L.; Ferhatosmanoğlu, Hakan; Matskin, M. (IEEE, 2017-05-06)
      Among different components of urban mobility, urban freight transport is usually considered as the least sustainable. Limited traffic infrastructures and increasing demands in dense urban regions lead to frequent delivery ...
    • Understanding the knowledge gaps of software engineers: an empirical analysis based on SWEBOK 

      Garousi, V.; Giray, G.; Tüzün, Eray (Association for Computing Machinery, 2019)
      Context: Knowledge level and productivity of the software engineering (SE) workforce are the subject of regular discussions among practitioners, educators, and researchers. There have been many efforts to measure and improve ...
    • Unification-based approach for knowledge base verification 

      Polat, F.; Guvenir, H. A. (1991)
      Knowledge base verification, a part of the validation process in expert system development, includes checking the knowledge base for completeness and consistency to guard against a variety of errors that can arise during ...
    • A unified graphics rendering pipeline for autostereoscopic rendering 

      Kalaiah, A.; Çapin, Tolga K. (IEEE, 2007-05)
      Autostereoscopic displays require rendering a scene from multiple viewpoints. The architecture of current-generation graphics processors are still grounded in the historic evolution of monoscopic rendering. In this paper, ...
    • Unsupervised classification of remotely sensed images using Gaussian mixture models and particle swarm optimization 

      Arı, Çağlar; Aksoy, Selim (IEEE, 2010)
      Gaussian mixture models (GMM) are widely used for un-supervised classification applications in remote sensing. Expectation-Maximization (EM) is the standard algorithm employed to estimate the parameters of these models. ...
    • Unsupervised concept drift detection with a discriminative classifier 

      Gözüaçık, Ömer; Büyükçakır, Alican; Bonab, H.; Can, Fazlı (Association for Computing Machinery, 2019)
      In data stream mining, one of the biggest challenges is to develop algorithms that deal with the changing data. As data evolve over time, static models become outdated. This phenomenon is called concept drift, and it is ...
    • Unsupervised detection and localization of structural textures using projection profiles 

      Yalniz, I. Z.; Aksoy, S. (Elsevier BV, 2010)
      The main goal of existing approaches for structural texture analysis has been the identification of repeating texture primitives and their placement patterns in images containing a single type of texture. We describe a ...
    • Unsupervised feature extraction via deep learning for histopathological classification of colon tissue images 

      Sari, C. T.; Gunduz Demir, C. (Institute of Electrical and Electronics Engineers, 2018)
      Histopathological examination is today’s gold standard for cancer diagnosis. However, this task is time consuming and prone to errors as it requires a detailed visual inspection and interpretation of a pathologist. ...
    • Unsupervised segmentation and classification of cervical cell images 

      Gençtav, A.; Aksoy, S.; Önder, S. (Elsevier BV, 2012-12)
      The Pap smear test is a manual screening procedure that is used to detect precancerous changes in cervical cells based on color and shape properties of their nuclei and cytoplasms. Automating this procedure is still an ...