Türkmen, Güzin

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Profile URL
https://hdl.handle.net/20.500.14411/7063
Name Variants
Tirkes G.
T.,Guzin
G.,Türkmen
T., Güzin
Güzin, Türkmen
G., Turkmen
Türkmen,G.
Tirkeş G.
Turkmen, Guzin
G.,Turkmen
T.,Güzin
Turkmen G.
Turkmen,G.
Guzin, Turkmen
Türkmen, Güzin
Türkmen G.
T., Guzin
Tirkes, Guzin
G., Türkmen
Job Title
Doktor Öğretim Üyesi
Email Address
guzin.turkmen@atilim.edu.tr
Main Affiliation
Computer Engineering
Status
Website
ORCID ID
0000-0003-0884-4876
Scopus Author ID
36020622300
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
G-9033-2019

Sustainable Development Goals

2

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11

SUSTAINABLE CITIES AND COMMUNITIES
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14

LIFE BELOW WATER
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6

CLEAN WATER AND SANITATION
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1

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5

GENDER EQUALITY
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9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
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16

PEACE, JUSTICE AND STRONG INSTITUTIONS
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17

PARTNERSHIPS FOR THE GOALS
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2

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15

LIFE ON LAND
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10

REDUCED INEQUALITIES
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7

AFFORDABLE AND CLEAN ENERGY
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8

DECENT WORK AND ECONOMIC GROWTH
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4

QUALITY EDUCATION
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4

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12

RESPONSIBLE CONSUMPTION AND PRODUCTION
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3

GOOD HEALTH AND WELL-BEING
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Documents

10

Citations

121

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4

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Documents

9

Citations

45

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Scholarly Output

23

Articles

9

Views / Downloads

90/279

Supervised MSc Theses

2

Supervised PhD Theses

0

WoS Citation Count

46

Scopus Citation Count

146

WoS h-index

3

Scopus h-index

5

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0

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0

WoS Citations per Publication

2.00

Scopus Citations per Publication

6.35

Open Access Source

5

Supervised Theses

2

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JournalCount
UBMK 2018 - 3rd International Conference on Computer Science and Engineering -- 3rd International Conference on Computer Science and Engineering, UBMK 2018 -- 20 September 2018 through 23 September 2018 -- Sarajevo -- 1435604
IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC -- 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC'07 -- 3 September 2007 through 7 September 2007 -- Athens -- 721052
3rd International Conference on Computer Science and Engineering (UBMK) -- SEP 20-23, 2018 -- Sarajevo, BOSNIA & HERCEG2
International Journal of Computational and Experimental Science and Engineering2
Turkish Online Journal of Educational Technology1
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Scholarly Output Search Results

Now showing 1 - 5 of 5
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 49
    Open Source Learning Management Systems in E-Learning and Moodle
    (2010) Aydin,C.C.; Tirkes,G.
    In the last decade, the effect of Internet usage in education has increased gradually and new technologies have improved student's learning. By using distance learning tools, the student education can be more flexible with respect to place and time constraints. So, students can access information in every time and everywhere either in libraries or during the lectures. As is widely known that, distance learning is costly, and cost-effectiveness becomes more important as the institutions become large-scale providers of distance education. Cost which is the most important disadvantages of distance learning according to traditional learning environments can be removed with the extensive features of the Open Source Software. Generalizing the usage of Open Source Software will provide development of learning tools and increases the educational quality. As far as the literature is reviewed, not much research has already been conducted about the comparisons of open source learning management systems in distance education. In this study, some analyses and comparisons were made about open source learning management systems and Moodle was outstanding with many features among other LMS that aims to improve the educational quality and include the tools that an e-learning system should have. © 2010 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.
  • Thumbnail Image
    Conference Object
    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.
  • Thumbnail Image
    Conference Object
    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.
  • Thumbnail Image
    Conference Object
    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.