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Browsing by Author "Bostan,A."

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    Citation - Scopus: 1
    Analyzing the Requirements for E-Government Transition of Iraqi Ics Services: an Iraqi Correction Services Case Study
    (Institute of Electrical and Electronics Engineers Inc., 2017) Alameri,M.A.; Bostan,A.; Akman,I.
    Iraqi Correction Services (ICS) is a department within the Ministry of Justice. Most services are provided through traditional paper and pen system. This system causes delays in service provision time and work over-load on ICS staff which translates into a high cost of service provision. E-government applications represent an opportunity to automate governmental services while improving both effectiveness and efficiency. This work presents the approach taken to determine the priority to automate ICS service from the perspective of service beneficiaries. The research is yet to be completed, however, up to this point we developed four different questionnaire-sets in order to collect the requirements from the shareholders, verified them and implemented the actual survey in the field. The experience gained throughout these steps and the future analysis plan is reported in this paper. © 2017 IEEE.
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    Deep Learning and Current Trends in Machine Learning
    (Institute of Electrical and Electronics Engineers Inc., 2018) Bostan,A.; Ekin,C.; Sengul,G.; Karakaya,M.; Tirkes,G.
    Academic interest and commercial attention can be used to identify how much potential a novel technology may have. Since the prospective advantages in it may help solving some problems that are not solved yet or improving the performance of readily available ones. In this study, we have investigated the Web of Science (WOS) indexing service database for the publications on Deep Learning (DL), Machine Learning (ML), Convolutional Neural Networks (CNN), and Image Processing to reveal out the current trend. The figures indicate the strong potential in DL approach especially in image processing domain. © 2018 IEEE.
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    Deep Learning and Current Trends in Machine Learning
    (Institute of Electrical and Electronics Engineers Inc., 2018) Bostan,A.; Ekin,C.; Sengul,G.; Karakaya,M.; Tirkes,G.
    Academic interest and commercial attention can be used to identify how much potential a novel technology may have. Since the prospective advantages in it may help solving some problems that are not solved yet or improving the performance of readily available ones. In this study, we have investigated the Web of Science (WOS) indexing service database for the publications on Deep Learning (DL), Machine Learning (ML), Convolutional Neural Networks (CNN), and Image Processing to reveal out the current trend. The figures indicate the strong potential in DL approach especially in image processing domain. © 2018 IEEE.
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    Citation - Scopus: 2
    An Undergraduate Curriculum for Deep Learning
    (Institute of Electrical and Electronics Engineers Inc., 2018) Tirkes,G.; Ekin,C.C.; Engul,G.; Bostan,A.; Karakaya,M.
    Deep Learning (DL) is an interesting and rapidly developing field of research which has been currently utilized as a part of industry and in many disciplines to address a wide range of problems, from image classification, computer vision, video games, bioinformatics, and handwriting recognition to machine translation. The starting point of this study is the recognition of a big gap between the sector need of specialists in DL technology and the lack of sufficient education provided by the universities. Higher education institutions are the best environment to provide this expertise to the students. However, currently most universities do not provide specifically designed DL courses to their students. Thus, the main objective of this study is to design a novel curriculum including two courses to facilitate teaching and learning of DL topic. The proposed curriculum will enable students to solve real-world problems by applying DL approaches and gain necessary background to adapt their knowledge to more advanced, industry-specific fields. © 2018 IEEE.
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    An Undergraduate Curriculum for Deep Learning
    (Institute of Electrical and Electronics Engineers Inc., 2018) Tirkes,G.; Ekin,C.C.; Engul,G.; Bostan,A.; Karakaya,M.
    Deep Learning (DL) is an interesting and rapidly developing field of research which has been currently utilized as a part of industry and in many disciplines to address a wide range of problems, from image classification, computer vision, video games, bioinformatics, and handwriting recognition to machine translation. The starting point of this study is the recognition of a big gap between the sector need of specialists in DL technology and the lack of sufficient education provided by the universities. Higher education institutions are the best environment to provide this expertise to the students. However, currently most universities do not provide specifically designed DL courses to their students. Thus, the main objective of this study is to design a novel curriculum including two courses to facilitate teaching and learning of DL topic. The proposed curriculum will enable students to solve real-world problems by applying DL approaches and gain necessary background to adapt their knowledge to more advanced, industry-specific fields. © 2018 IEEE.
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    Yazilim Mühendisligi Egitiminde Bitirme Projesinin Yürütülmesinde İki Farkli Yöntemin Ögrenci Bakis Açisiyla Degerlendirilmesi
    (CEUR-WS, 2015) Karakaya,M.; Bostan,A.
    [No abstract available]
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    Yazilim Mühendisliʇi Eʇitiminde Bitirme Projesi Dersinin Öʇrenci Bakiş Açisiyla Deʇerlendirilmesi
    (CEUR-WS, 2013) Karakaya,M.; Bostan,A.
    [No abstract available]
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