Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Subject: search.filters.subject.Software engineeringWoS Q: search.filters.wosQuartile.N/A

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  • Conference Object
    Citation - Scopus: 5
    Effort Estimation Methods for Erp Projects Based on Function Points: a Case Study
    (Association for Computing Machinery (ACM), 2017) Küçükateş Ömüral, Neslihan; Demirörs, Onur
    Enterprise Resource Planning (ERP) Systems evolve at a rapid pace based on customer and industry expectations. As a result, historic project data for these kinds of projects lose their value especially for analogy based estimation methods. In this rapidly evolving domain, function point based methods might provide a sound alternative for ERP effort estimation. This paper presents the results obtained by applying three methods published in the literature in which function points are used as an input for ERP effort estimation. The evaluation of these methods with respect to their measurement processes and estimation errors are presented; their advantages and disadvantages are discussed.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 2
    A Case Study on Logging Visual Activities: Chess Game
    (Springer Verlag, 2006) Ozan, Şükrü; Gümüştekin, Şevket
    Automatically recognizing and analyzing visual activities in complex environments is a challenging and open-ended problem. In this study this task is performed in a chess game scenario where the rules, actions and the environment are well defined. The purpose here is to detect and observe a FIDE (Fédération International des Ėchecs) compatible chess board, generating a log file of the moves made by human players. A series of basic image processing operations have been applied to perform the desired task. The first step of automatically detecting a chess board is followed by locating the positions of the pieces. After the initial setup is established every move made by a player is automatically detected and verified. Intel® Open Source Computer Vision Library (OpenCV) is used in the current software implementation.